Protocol

SugarBase taxonomy · Species (GlycanML taxonomy prediction)

GlycanML Species · Table 3, p. 8. Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

Sources

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, p. 8, Species

22 evaluations · 22 metric rows

At a glance

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-17. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Data, procedure and scoring
Property	Description and evidence
Datasets	Not extracted or verified for this record.
Organisms	Not extracted or verified for this record.
Assays	Not extracted or verified for this record.
Splits	Not extracted or verified for this record.
Allowed inputs	Not extracted or verified for this record.
Adaptation	Not extracted or verified for this record.
Metrics	Not extracted or verified for this record.
Baselines	Not extracted or verified for this record.

How it works

Evaluation in this paper

Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

Sources

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, p. 8, Species

Evaluation design

Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.

Benchmarks

GlycanML

Tasks

GlycanML taxonomy prediction

These source-backed links do not make different protocols or scores interchangeable.

Recorded evaluations

Each evaluation records what was tested and under which conditions.

Explore all linked results

Published comparisons

Explore the results reported under one evaluation protocol. Each figure keeps its source, dataset and metric together; it is not a ranking across studies.

Comparison and metric

GlycanML Species · Table 3, p. 8

accuracy (percent) · Higher values are better for this metric.

Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

Evaluation protocol · SugarBase taxonomy · Species

Shallow CNN · Configuration · Author-reported evaluation33.70(1.12)
ResNet · Configuration · Author-reported evaluation26.59(1.89)
LSTM · Configuration · Author-reported evaluation26.04(1.73)
Transformer · Configuration · Author-reported evaluation27.49(1.20)
GCN · Configuration · Author-reported evaluation31.01(0.87)
GAT · Configuration · Author-reported evaluation34.13(0.99)
GIN · Configuration · Author-reported evaluation31.85(2.19)
MPNN · Configuration · Author-reported evaluation33.80(1.87)
RGCN · Configuration · Author-reported evaluation38.12(1.15)
CompGCN · Configuration · Author-reported evaluation40.04(1.32)

Source order is preserved. Plotted marks show point estimates; uncertainty, where reported, is retained in the printed values and table. Differences do not establish statistical significance.

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, p. 8, Species

Values, uncertainty and evidence

accuracy: original source values
Tested entity	Printed value	Uncertainty	Evidence
Shallow CNN · Configuration	33.70(1.12) percent	type: standard_deviation; value: 1.12; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row Shallow CNN, column Species
ResNet · Configuration	26.59(1.89) percent	type: standard_deviation; value: 1.89; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row ResNet, column Species
LSTM · Configuration	26.04(1.73) percent	type: standard_deviation; value: 1.73; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row LSTM, column Species
Transformer · Configuration	27.49(1.20) percent	type: standard_deviation; value: 1.2; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row Transformer, column Species
GCN · Configuration	31.01(0.87) percent	type: standard_deviation; value: 0.87; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GCN, column Species
GAT · Configuration	34.13(0.99) percent	type: standard_deviation; value: 0.99; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GAT, column Species
GIN · Configuration	31.85(2.19) percent	type: standard_deviation; value: 2.19; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GIN, column Species
MPNN · Configuration	33.80(1.87) percent	type: standard_deviation; value: 1.87; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row MPNN, column Species
RGCN · Configuration	38.12(1.15) percent	type: standard_deviation; value: 1.15; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row RGCN, column Species
CompGCN · Configuration	40.04(1.32) percent	type: standard_deviation; value: 1.32; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row CompGCN, column Species

Scope and limitations

Taxonomic levels are distinct tasks; do not combine raw accuracy across levels.
Protein–glycan scores evaluate combined glycan encoders plus ESM-1b/MLP, not an ESM-1b standalone checkpoint.
Cluster manifests and trained checkpoint hashes are not enumerated in the paper table.

Source transcription and grouping reviewed by automated source review on 2026-09-17. These experiments were not independently reproduced by rewire.

Tested entities and results

Release 2026-09-17-d277315f7d76 · 22 evaluations · 22 metric rows. Different protocols are not a single leaderboard.

Evaluation setupMetricEvidence origin

Results grouped by the exact reported evaluation
Metric and finding	Coverage and uncertainty	Evidence
Transformer: SugarBase taxonomy · Species Configuration: TransformerProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
27.49(1.20)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.2; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row Transformer, column Species Source checking is not independent reproduction.
Shallow CNN / DTP: SugarBase taxonomy · Species Configuration: Shallow CNN / DTPProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
36.02(1.23)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.23; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DTP, column Species Source checking is not independent reproduction.
GAT: SugarBase taxonomy · Species Configuration: GATProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
34.13(0.99)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.99; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GAT, column Species Source checking is not independent reproduction.
Shallow CNN / N-MTL: SugarBase taxonomy · Species Configuration: Shallow CNN / N-MTLProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
36.74(0.35)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.35; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, N-MTL, column Species Source checking is not independent reproduction.
RGCN / TS: SugarBase taxonomy · Species Configuration: RGCN / TSProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
43.31(0.29)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.29; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, TS, column Species Source checking is not independent reproduction.
RGCN / DWA: SugarBase taxonomy · Species Configuration: RGCN / DWAProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
37.47(0.44)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.44; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, DWA, column Species Source checking is not independent reproduction.
RGCN: SugarBase taxonomy · Species Configuration: RGCNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
38.12(1.15)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.15; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row RGCN, column Species Source checking is not independent reproduction.
Shallow CNN / DWA: SugarBase taxonomy · Species Configuration: Shallow CNN / DWAProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
33.04(0.95)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.95; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DWA, column Species Source checking is not independent reproduction.
MPNN: SugarBase taxonomy · Species Configuration: MPNNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
33.80(1.87)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.87; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row MPNN, column Species Source checking is not independent reproduction.
ResNet: SugarBase taxonomy · Species Configuration: ResNetProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
26.59(1.89)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.89; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row ResNet, column Species Source checking is not independent reproduction.
RGCN / GN: SugarBase taxonomy · Species Configuration: RGCN / GNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
38.67(1.52)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.52; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, GN, column Species Source checking is not independent reproduction.
Shallow CNN / TS: SugarBase taxonomy · Species Configuration: Shallow CNN / TSProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
35.84(1.20)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.2; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, TS, column Species Source checking is not independent reproduction.
Shallow CNN / UW: SugarBase taxonomy · Species Configuration: Shallow CNN / UWProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
34.78(1.11)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.11; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, UW, column Species Source checking is not independent reproduction.
RGCN / UW: SugarBase taxonomy · Species Configuration: RGCN / UWProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
39.61(0.89)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.89; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, UW, column Species Source checking is not independent reproduction.
Shallow CNN: SugarBase taxonomy · Species Configuration: Shallow CNNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
33.70(1.12)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.12; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row Shallow CNN, column Species Source checking is not independent reproduction.
RGCN / DTP: SugarBase taxonomy · Species Configuration: RGCN / DTPProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
39.97(2.11)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 2.11; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, DTP, column Species Source checking is not independent reproduction.
CompGCN: SugarBase taxonomy · Species Configuration: CompGCNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
40.04(1.32)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.32; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row CompGCN, column Species Source checking is not independent reproduction.
GCN: SugarBase taxonomy · Species Configuration: GCNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
31.01(0.87)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.87; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GCN, column Species Source checking is not independent reproduction.
RGCN / N-MTL: SugarBase taxonomy · Species Configuration: RGCN / N-MTLProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
38.59(1.44)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.44; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, N-MTL, column Species Source checking is not independent reproduction.
Shallow CNN / GN: SugarBase taxonomy · Species Configuration: Shallow CNN / GNProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
36.49(1.63)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.63; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, GN, column Species Source checking is not independent reproduction.
GIN: SugarBase taxonomy · Species Configuration: GINProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
31.85(2.19)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 2.19; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row GIN, column Species Source checking is not independent reproduction.
LSTM: SugarBase taxonomy · Species Configuration: LSTMProtocol: SugarBase taxonomy · Species (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Species Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Author-reported evaluation · Evaluation metadata: needs review
26.04(1.73)% accuracy Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 1.73; n: 3; unit: same as metric Scored: Not reported · Eligible: Not reported	source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 3, row LSTM, column Species Source checking is not independent reproduction.

Papers and result coverage

Last literature check: 2026-09-17. Primary-paper within-study comparison; numerical results not independently reproduced.

Paper or primary resource	Version	Reference
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning	arXiv:2405.16206v1, 2024-05-25	Read source

What is still missing

Paper table does not enumerate trained checkpoint hashes; source configuration names retained.

Search and extraction details

complete comparison extracted

Searches

GlycanML benchmark 2405.16206

Evidence locations

Table 3, p. 8, Species

Strengths and limitations

Strengths and considerations

No source-reviewed explanatory claims are recorded here yet.

Limitations and conditions

No source-reviewed explanatory claims are recorded here yet.

Profile review details

Primary-source transcription and separate automated review. No human sign-off or experimental reproduction.

Stable record: paper-protocol-0d66c7cabff9d799d5

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

4 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-d277315f7d76
Property and statement	Original source and location	Review and provenance
Evaluation in this paper Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Individual claims	GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning Original source ↗ Table 3, p. 8, Species Version: arXiv:2405.16206v1, 2024-05-25 Retrieved: 2026-09-16T21:04:56.017006+00:00	source checked automated source review · 2026-09-17 Audit details Primary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: `attributes.profile.sections.0.body` Source artifact SHA-256: `9ba3db678b4550898a612b42e8832bf9dee40935090fc4d969ba8f6ac5106979` Hash scope: Exact retrieved primary paper artifact bytes. Inspected artifact
Introduction GlycanML Species · Table 3, p. 8. Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Individual claims	GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning Original source ↗ Table 3, p. 8, Species Version: arXiv:2405.16206v1, 2024-05-25 Retrieved: 2026-09-16T21:04:56.017006+00:00	source checked automated source review · 2026-09-17 Audit details Primary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: `attributes.profile.summary` Source artifact SHA-256: `9ba3db678b4550898a612b42e8832bf9dee40935090fc4d969ba8f6ac5106979` Hash scope: Exact retrieved primary paper artifact bytes. Inspected artifact
Relationship: evaluates task discovery-benchmark-glycanml-taxonomy-prediction Individual claims	GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning Original source ↗ Table 3, p. 8, Species Version: arXiv:2405.16206v1, 2024-05-25 Retrieved: 2026-09-16T21:04:56.017006+00:00	source checked automated source review · 2026-09-17 Audit details Field: `links:evaluates_task:discovery-benchmark-glycanml-taxonomy-prediction` Claim: paper-claim-4919d53b45fe22628a Source artifact SHA-256: `9ba3db678b4550898a612b42e8832bf9dee40935090fc4d969ba8f6ac5106979` Hash scope: Exact retrieved primary paper artifact bytes. Inspected artifact
Relationship: part of discovery-benchmark-glycanml Individual claims	GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning Original source ↗ Table 3, p. 8, Species Version: arXiv:2405.16206v1, 2024-05-25 Retrieved: 2026-09-16T21:04:56.017006+00:00	source checked automated source review · 2026-09-17 Audit details Field: `links:part_of:discovery-benchmark-glycanml` Claim: paper-claim-f1b642070a9eaa7622 Source artifact SHA-256: `9ba3db678b4550898a612b42e8832bf9dee40935090fc4d969ba8f6ac5106979` Hash scope: Exact retrieved primary paper artifact bytes. Inspected artifact

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Sources and history

Release 2026-09-17-d277315f7d76 · Record review: needs review

1 source records and release history

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Original source · arXiv:2405.16206v1, 2024-05-25

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Technical metadata and extraction receipts

Stable ID: paper-protocol-0d66c7cabff9d799d5

areas: glycomics
entity level: protocol
protocol: Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.
comparison panels: id: glycanml-v1-single-species; title: GlycanML Species · Table 3, p. 8; protocol id: paper-protocol-0d66c7cabff9d799d5; dataset id: paper-dataset-4c48251022ccb53313; metric: accuracy; unit: percent; direction: higher; result ids: paper-result-dc5501dc1954b54a36; paper-result-825d6b6597e463e7cc; paper-result-fedc9b0d7fadb8f74e; paper-result-19f2505d003bc76dcc; paper-result-e9a6b117f8a49863be; paper-result-33876cb9abd2083b08; paper-result-fad4c5f6d2c179bb3f; paper-result-77f9c63846886893da; paper-result-723b93ccacba688198; paper-result-e74c30428cded73273; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 3, p. 8, Species; context: Author-reported single-task models on the same held-out task; not a cross-paper ranking. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.; caveats: Taxonomic levels are distinct tasks; do not combine raw accuracy across levels.; Protein–glycan scores evaluate combined glycan encoders plus ESM-1b/MLP, not an ESM-1b standalone checkpoint.; Cluster manifests and trained checkpoint hashes are not enumerated in the paper table.; review: method: automated_source_review; date: 2026-09-17; id: glycanml-v1-mtl-0-species; title: GlycanML Species · Table 4, p. 9; protocol id: paper-protocol-0d66c7cabff9d799d5; dataset id: paper-dataset-4c48251022ccb53313; metric: accuracy; unit: percent; direction: higher; result ids: paper-result-dc5501dc1954b54a36; paper-result-3decc92d3c4b47daaa; paper-result-efe8061d8b717b3d06; paper-result-994aa15ef63ab963bd; paper-result-af7e44b66703958045; paper-result-7741da71a6bffbfe05; paper-result-2a425531358cee050f; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 4, p. 9, Species; context: Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.; caveats: Mean accuracy is an unweighted aggregate of eight taxonomic tasks as reported; keep separate from every individual level.; The six MTL approaches change training, so do not label their scores as the base encoder alone.; review: method: automated_source_review; date: 2026-09-17; id: glycanml-v1-mtl-1-species; title: GlycanML Species · Table 4, p. 9; protocol id: paper-protocol-0d66c7cabff9d799d5; dataset id: paper-dataset-4c48251022ccb53313; metric: accuracy; unit: percent; direction: higher; result ids: paper-result-723b93ccacba688198; paper-result-ec8c144273ccc0a850; paper-result-928828d65bf0d96282; paper-result-5f765144a6d6d5bdb4; paper-result-dc366357aed61c1324; paper-result-618be13e9cdea80f33; paper-result-e3de6f13924b3f0956; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 4, p. 9, Species; context: Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.; caveats: Mean accuracy is an unweighted aggregate of eight taxonomic tasks as reported; keep separate from every individual level.; The six MTL approaches change training, so do not label their scores as the base encoder alone.; review: method: automated_source_review; date: 2026-09-17
benchmark research: review date: 2026-09-17; status: complete_comparison_extracted; primary sources: expansion-p3-glycanml-2405-16206v1; inspected locators: Table 3, p. 8, Species; searched queries: GlycanML benchmark 2405.16206; gaps: Paper table does not enumerate trained checkpoint hashes; source configuration names retained.; claim scope: Primary-paper within-study comparison; numerical results not independently reproduced.
legacy kinds: benchmark
entity classification: review date: 2026-09-17; rationale: The source-backed record identifies a specified evaluated procedure and its dataset/split/scoring context. Classify it as a protocol while preserving version and comparison restrictions.; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 3, p. 8, Species; ambiguities: None recorded

Related records

evaluates task: GlycanML taxonomy prediction
part of: GlycanML
subject: SugarBase taxonomy · Species (GlycanML taxonomy prediction): links:evaluates_task:discovery-benchmark-glycanml-taxonomy-prediction
subject: SugarBase taxonomy · Species (GlycanML taxonomy prediction): links:part_of:discovery-benchmark-glycanml
benchmark: GCN: SugarBase taxonomy · Species
benchmark: RGCN: SugarBase taxonomy · Species
benchmark: Shallow CNN / N-MTL: SugarBase taxonomy · Species
benchmark: RGCN / GN: SugarBase taxonomy · Species
benchmark: RGCN / UW: SugarBase taxonomy · Species
benchmark: RGCN / N-MTL: SugarBase taxonomy · Species
benchmark: CompGCN: SugarBase taxonomy · Species
benchmark: Shallow CNN / DWA: SugarBase taxonomy · Species
benchmark: Shallow CNN / UW: SugarBase taxonomy · Species
benchmark: Shallow CNN / GN: SugarBase taxonomy · Species
benchmark: Transformer: SugarBase taxonomy · Species
benchmark: RGCN / DTP: SugarBase taxonomy · Species
benchmark: RGCN / DWA: SugarBase taxonomy · Species
benchmark: GIN: SugarBase taxonomy · Species
benchmark: MPNN: SugarBase taxonomy · Species
benchmark: Shallow CNN / DTP: SugarBase taxonomy · Species
benchmark: RGCN / TS: SugarBase taxonomy · Species
benchmark: Shallow CNN / TS: SugarBase taxonomy · Species
benchmark: ResNet: SugarBase taxonomy · Species
benchmark: LSTM: SugarBase taxonomy · Species
benchmark: Shallow CNN: SugarBase taxonomy · Species
benchmark: GAT: SugarBase taxonomy · Species

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