This GlycanML task evaluates glycosylation-type classification using glycan representations.
Explanatory profile: source reviewed · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Datasets | N-linked, O-linked and free glycan classes.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Splits | Glycans are represented by motif frequencies and clustered; motif groups are allocated to training, validation and test in an 8:1:1 grouping scheme. Table 1 preserves the resulting dataset-specific counts.Sourcesglycanml primary benchmark evidence · Sections 3.1–3.3; Table 1 |
| Metrics | Accuracy and Matthews correlation coefficient in the checked three-class configuration.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Baselines | Sequence-model CNN, ResNet, LSTM and BERT configurations; graph-model GCN, RGCN, GAT, GIN, CompGCN and MPNN configurations.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Leakage controls | Motif-based cluster separation tests transfer to structurally different glycans. This is a glycan-structure control, not a claim that all organisms or source studies are held out.Sourcesglycanml primary benchmark evidence · Sections 3.1–3.3; Table 1 |
| Uncertainty | Every experiment uses seeds 0, 1 and 2; reported summaries are the mean and standard deviation over those three runs.Sourcesglycanml primary benchmark evidence · Sections 3.1–3.4 and 5.1; Tables 1 and 3 |
| Entity type | Constituent benchmark task: GlycanML glycosylation type predictionSources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Organisms | Taxonomy tasks explicitly predict organism categories; species scope depends on the constituent dataset.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Assays | Taxonomy, immunogenicity, glycosylation-type and protein–glycan interaction annotations.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Allowed inputs | Glycan sequence or graph representation with a glycosylation-type target.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
| Adaptation | Separate single-task and multi-task training configurations are supplied.Sources (3)GlycanML/GlycanML official source; GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml; GlycanML/GlycanML module/custom_datasets/glycan_link.py · Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods) |
Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions.
N-linked, O-linked and free glycan classes. Dataset loader retains the train/validation/test assignments supplied in the downloaded CSV; this inspection does not establish how those original assignments were constructed. Accuracy and Matthews correlation coefficient in the checked three-class configuration. Sequence-model CNN, ResNet, LSTM and BERT configurations; graph-model GCN, RGCN, GAT, GIN, CompGCN and MPNN configurations.
Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.
These source-backed links do not make different protocols or scores interchangeable.
Explore the results reported under one evaluation protocol. Each figure keeps its source, dataset and metric together; it is not a ranking across studies.
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. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column.
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, Glycos| Tested entity | Printed value | Uncertainty | Evidence |
|---|---|---|---|
| Shallow CNN · Configuration | 97.22(0.44) percent | type: standard_deviation; value: 0.44; 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 Glycos |
| ResNet · Configuration | 98.55(0.58) percent | type: standard_deviation; value: 0.58; 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 Glycos |
| LSTM · Configuration | 96.28(1.42) percent | type: standard_deviation; value: 1.42; 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 Glycos |
| Transformer · Configuration | 95.90(1.45) percent | type: standard_deviation; value: 1.45; 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 Glycos |
| GCN · Configuration | 95.90(0.11) percent | type: standard_deviation; value: 0.11; 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 Glycos |
| GAT · Configuration | 94.63(0.39) percent | type: standard_deviation; value: 0.39; 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 Glycos |
| GIN · Configuration | 97.16(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 3, row GIN, column Glycos |
| MPNN · Configuration | 97.41(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 3, row MPNN, column Glycos |
| RGCN · Configuration | 95.14(2.21) percent | type: standard_deviation; value: 2.21; 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 Glycos |
| CompGCN · Configuration | 94.38(3.13) percent | type: standard_deviation; value: 3.13; 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 Glycos |
Source transcription and grouping reviewed by automated source review on 2026-09-17. These experiments were not independently reproduced by rewire.
Release 2026-09-17-d277315f7d76 · 10 evaluations · 10 metric rows. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| MPNN: GlyConnect glycosylation · Glycos Configuration: MPNNProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 97.41(0.90)% accuracy 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 3, row MPNN, column Glycos Source checking is not independent reproduction. |
| GIN: GlyConnect glycosylation · Glycos Configuration: GINProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 97.16(0.19)% accuracy 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 3, row GIN, column Glycos Source checking is not independent reproduction. |
| RGCN: GlyConnect glycosylation · Glycos Configuration: RGCNProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 95.14(2.21)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 2.21; 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 3, row RGCN, column Glycos Source checking is not independent reproduction. |
| CompGCN: GlyConnect glycosylation · Glycos Configuration: CompGCNProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 94.38(3.13)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 3.13; 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 Glycos Source checking is not independent reproduction. |
| LSTM: GlyConnect glycosylation · Glycos Configuration: LSTMProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 96.28(1.42)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 1.42; 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 3, row LSTM, column Glycos Source checking is not independent reproduction. |
| ResNet: GlyConnect glycosylation · Glycos Configuration: ResNetProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 98.55(0.58)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 0.58; 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 Glycos Source checking is not independent reproduction. |
| Transformer: GlyConnect glycosylation · Glycos Configuration: TransformerProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 95.90(1.45)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 1.45; 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 3, row Transformer, column Glycos Source checking is not independent reproduction. |
| GAT: GlyConnect glycosylation · Glycos Configuration: GATProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 94.63(0.39)% accuracy 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 3, row GAT, column Glycos Source checking is not independent reproduction. |
| GCN: GlyConnect glycosylation · Glycos Configuration: GCNProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 95.90(0.11)% accuracy Unit: percent · Direction: higher | Uncertainty: type: standard deviation; value: 0.11; 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 3, row GCN, column Glycos Source checking is not independent reproduction. |
| Shallow CNN: GlyConnect glycosylation · Glycos Configuration: Shallow CNNProtocol: GlyConnect glycosylation · Glycos (GlycanML glycosylation type prediction)Dataset: GlyConnect glycosylation · Glycos Author-reported single-task models on the same held-out task; not a cross-paper ranking. Taxonomy, immunogenicity and glycosylation: motif-frequency K-means cluster allocation 8:1:1. Interaction: MMseqs2 protein clusters at minimum identity 0.5 allocated 8:1:1. Exact counts are attached to each column. Author-reported evaluation · Evaluation metadata: needs review | ||
| 97.22(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 3, row Shallow CNN, column Glycos Source checking is not independent reproduction. |
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 |
complete comparison extracted
Primary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction.
Stable record: discovery-benchmark-glycanml-glycosylation-type-predictionTrace 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.
50 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims | GlycanML/GlycanML module/custom_datasets/glycan_link.py Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims | GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims | glycanml primary benchmark evidence Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2405.16206v1 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram caption Conceptual procedure. Task variants and protocol versions retain their separate scoring conditions. Individual claims | GlycanML/GlycanML official source Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Allowed inputs: Glycan sequence or graph representation with a glycosylation-type target.","Splits: Glycans are represented by motif frequencies and clustered; motif groups are allocated to training, validation and test in an 8:1:1 grouping scheme. Table 1 preserves the resulting dataset-specific counts.","Metrics: Accuracy and Matthews correlation coefficient in the checked three-class configuration."] Individual claims | GlycanML/GlycanML module/custom_datasets/glycan_link.py Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Allowed inputs: Glycan sequence or graph representation with a glycosylation-type target.","Splits: Glycans are represented by motif frequencies and clustered; motif groups are allocated to training, validation and test in an 8:1:1 grouping scheme. Table 1 preserves the resulting dataset-specific counts.","Metrics: Accuracy and Matthews correlation coefficient in the checked three-class configuration."] Individual claims | GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Allowed inputs: Glycan sequence or graph representation with a glycosylation-type target.","Splits: Glycans are represented by motif frequencies and clustered; motif groups are allocated to training, validation and test in an 8:1:1 grouping scheme. Table 1 preserves the resulting dataset-specific counts.","Metrics: Accuracy and Matthews correlation coefficient in the checked three-class configuration."] Individual claims | glycanml primary benchmark evidence Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2405.16206v1 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Allowed inputs: Glycan sequence or graph representation with a glycosylation-type target.","Splits: Glycans are represented by motif frequencies and clustered; motif groups are allocated to training, validation and test in an 8:1:1 grouping scheme. Table 1 preserves the resulting dataset-specific counts.","Metrics: Accuracy and Matthews correlation coefficient in the checked three-class configuration."] Individual claims | GlycanML/GlycanML official source Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluation procedure Individual claims | GlycanML/GlycanML module/custom_datasets/glycan_link.py Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluation procedure Individual claims | GlycanML/GlycanML configs/single_task/BERT/link_BERT.yaml Pinned README: Introduction; Experiment configurations; leaderboard; pinned configs/single_task/BERT/link_BERT.yaml, module/custom_datasets/glycan_link.py (task metric, dataset class and split methods); Sections 3.1–3.3; Table 1 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 9f392aa6f9c6d74a296a250199beb347923d04e0 | source checked automated source review · 2026-09-16 Audit detailsPrimary paper and/or task implementation reviewed for the explicitly cited methodology claims. Scope-limited absence is recorded only after the documented source search; no model runs or independent reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-09-17-d277315f7d76 · Record review: discovered
Stable ID: discovery-benchmark-glycanml-glycosylation-type-prediction