Protocol

SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)

GlycanML Mean Acc (%) · Table 4, p. 9. Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, p. 9, Mean Acc (%)

14 evaluations · 14 metric rows

At a glance

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.

How it works

Evaluation in this paper

Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, p. 9, Mean Acc (%)

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 Mean Acc (%) · Table 4, p. 9

mean accuracy across eight taxonomy tasks (percent) · Higher values are better for this metric.

Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.

Evaluation protocol · SugarBase taxonomy · Mean Acc

Shallow CNN · Configuration · Author-reported evaluation63.47(0.42)
Shallow CNN / N-MTL · Configuration · Author-reported evaluation63.49(0.55)
Shallow CNN / GN · Configuration · Author-reported evaluation63.13(0.25)
Shallow CNN / TS · Configuration · Author-reported evaluation63.77(0.19)
Shallow CNN / UW · Configuration · Author-reported evaluation62.87(0.87)
Shallow CNN / DWA · Configuration · Author-reported evaluation61.88(0.90)
Shallow CNN / DTP · Configuration · Author-reported evaluation62.83(0.45)

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 4, p. 9, Mean Acc (%)

Values, uncertainty and evidence

mean accuracy across eight taxonomy tasks: original source values
Tested entity	Printed value	Uncertainty	Evidence
Shallow CNN · Configuration	63.47(0.42) percent	type: standard_deviation; value: 0.42; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, Single-Task, column Mean Acc (%)
Shallow CNN / N-MTL · Configuration	63.49(0.55) percent	type: standard_deviation; value: 0.55; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, N-MTL, column Mean Acc (%)
Shallow CNN / GN · Configuration	63.13(0.25) percent	type: standard_deviation; value: 0.25; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, GN, column Mean Acc (%)
Shallow CNN / TS · Configuration	63.77(0.19) percent	type: standard_deviation; value: 0.19; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, TS, column Mean Acc (%)
Shallow CNN / UW · Configuration	62.87(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 4, Shallow CNN, UW, column Mean Acc (%)
Shallow CNN / DWA · Configuration	61.88(0.90) percent	type: standard_deviation; value: 0.9; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DWA, column Mean Acc (%)
Shallow CNN / DTP · Configuration	62.83(0.45) percent	type: standard_deviation; value: 0.45; n: 3; unit: same_as_metric	Author-reported evaluation · source checkedGlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DTP, column Mean Acc (%)

Scope and limitations

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.

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 · 14 evaluations · 14 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
Shallow CNN / UW: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / UWProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
62.87(0.87)% mean accuracy across eight taxonomy tasks 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 4, Shallow CNN, UW, column Mean Acc (%) Source checking is not independent reproduction.
RGCN / N-MTL: SugarBase taxonomy · Mean Acc Configuration: RGCN / N-MTLProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
64.45(0.40)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.4; 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 Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN / GN: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / GNProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.13(0.25)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.25; 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 Mean Acc (%) Source checking is not independent reproduction.
RGCN / TS: SugarBase taxonomy · Mean Acc Configuration: RGCN / TSProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
66.68(0.23)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.23; 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, RGCN, TS, column Mean Acc (%) Source checking is not independent reproduction.
RGCN / GN: SugarBase taxonomy · Mean Acc Configuration: RGCN / GNProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.83(0.65)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.65; 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 Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN / DTP: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / DTPProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
62.83(0.45)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.45; 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 Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN / N-MTL: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / N-MTLProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.49(0.55)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.55; 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 Mean Acc (%) Source checking is not independent reproduction.
RGCN / UW: SugarBase taxonomy · Mean Acc Configuration: RGCN / UWProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
64.90(0.39)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.39; 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 Mean Acc (%) Source checking is not independent reproduction.
RGCN / DWA: SugarBase taxonomy · Mean Acc Configuration: RGCN / DWAProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.65(0.25)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.25; 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 Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN / TS: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / TSProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.77(0.19)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.19; 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 4, Shallow CNN, TS, column Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN: SugarBase taxonomy · Mean Acc Configuration: Shallow CNNProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
63.47(0.42)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.42; 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, Single-Task, column Mean Acc (%) Source checking is not independent reproduction.
RGCN: SugarBase taxonomy · Mean Acc Configuration: RGCNProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
65.05(0.21)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.21; 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, Single-Task, column Mean Acc (%) Source checking is not independent reproduction.
Shallow CNN / DWA: SugarBase taxonomy · Mean Acc Configuration: Shallow CNN / DWAProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
61.88(0.90)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.9; 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 Mean Acc (%) Source checking is not independent reproduction.
RGCN / DTP: SugarBase taxonomy · Mean Acc Configuration: RGCN / DTPProtocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction)Dataset: SugarBase taxonomy · Mean Acc 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
64.15(0.25)% mean accuracy across eight taxonomy tasks Unit: percent · Direction: higher	Uncertainty: type: standard deviation; value: 0.25; 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 Mean Acc (%) 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 4, p. 9, Mean Acc (%)

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-f6058db65ace02f920

Evidence table

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 Fixed backbone; compare adaptation strategies, not standalone foundation models. 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 4, p. 9, Mean Acc (%) 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 Mean Acc (%) · Table 4, p. 9. Fixed backbone; compare adaptation strategies, not standalone foundation models. 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 4, p. 9, Mean Acc (%) 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 4, p. 9, Mean Acc (%) 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-ea41624b29a444de06 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 4, p. 9, Mean Acc (%) 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-b03270379ecc7a0199 Source artifact SHA-256: `9ba3db678b4550898a612b42e8832bf9dee40935090fc4d969ba8f6ac5106979` Hash scope: Exact retrieved primary paper artifact bytes. Inspected artifact

All evidence (CSV)All evidence (JSONL)How to read the evidence

Sources and history

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

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

Download this release

Technical metadata and extraction receipts

Stable ID: paper-protocol-f6058db65ace02f920

areas: glycomics
entity level: protocol
protocol: Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1.
comparison panels: id: glycanml-v1-mtl-0-mean-acc; title: GlycanML Mean Acc (%) · Table 4, p. 9; protocol id: paper-protocol-f6058db65ace02f920; dataset id: paper-dataset-3b08dc110e25f5011e; metric: mean accuracy across eight taxonomy tasks; unit: percent; direction: higher; result ids: paper-result-3b8254d638b7cf840c; paper-result-26353885331e3500b0; paper-result-14f9374f43c9937375; paper-result-37820120325451b083; paper-result-010096d9a694ae3520; paper-result-96a241380ae6ba882a; paper-result-222b0816ea58c393cd; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 4, p. 9, Mean Acc (%); 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-mean-acc; title: GlycanML Mean Acc (%) · Table 4, p. 9; protocol id: paper-protocol-f6058db65ace02f920; dataset id: paper-dataset-3b08dc110e25f5011e; metric: mean accuracy across eight taxonomy tasks; unit: percent; direction: higher; result ids: paper-result-5ebd480b2815e83e3d; paper-result-13c2836aee0f4143ea; paper-result-19abc6d9c3e6eaf449; paper-result-16f47917baa3903d08; paper-result-2d85ed1325988db66d; paper-result-31eba8c1c674dcaf66; paper-result-ecd8e5a52b2ee62bca; source ids: expansion-p3-glycanml-2405-16206v1; source locator: Table 4, p. 9, Mean Acc (%); 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 4, p. 9, Mean Acc (%); 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 4, p. 9, Mean Acc (%); ambiguities: None recorded

Related records

evaluates task: GlycanML taxonomy prediction
part of: GlycanML
subject: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction): links:part_of:discovery-benchmark-glycanml
subject: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction): links:evaluates_task:discovery-benchmark-glycanml-taxonomy-prediction
benchmark: Shallow CNN / UW: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN / DTP: SugarBase taxonomy · Mean Acc
benchmark: RGCN / DWA: SugarBase taxonomy · Mean Acc
benchmark: RGCN / TS: SugarBase taxonomy · Mean Acc
benchmark: RGCN / UW: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN / DWA: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN / N-MTL: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN / TS: SugarBase taxonomy · Mean Acc
benchmark: RGCN / GN: SugarBase taxonomy · Mean Acc
benchmark: RGCN / N-MTL: SugarBase taxonomy · Mean Acc
benchmark: Shallow CNN / GN: SugarBase taxonomy · Mean Acc
benchmark: RGCN / DTP: SugarBase taxonomy · Mean Acc
benchmark: RGCN: SugarBase taxonomy · Mean Acc

Suggest a correction