| Configuration: Shallow CNN / UW | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 62.87(0.87)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.87; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / UW: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, UW, column Mean Acc (%) |
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| Configuration: RGCN / N-MTL | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 64.45(0.40)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.4; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / N-MTL: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, N-MTL, column Mean Acc (%) |
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| Configuration: Shallow CNN / GN | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.13(0.25)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.25; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / GN: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, GN, column Mean Acc (%) |
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| Configuration: RGCN / TS | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 66.68(0.23)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.23; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / TS: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, TS, column Mean Acc (%) |
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| Configuration: RGCN / GN | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.83(0.65)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.65; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / GN: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, GN, column Mean Acc (%) |
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| Configuration: Shallow CNN / DTP | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 62.83(0.45)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.45; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / DTP: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DTP, column Mean Acc (%) |
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| Configuration: Shallow CNN / N-MTL | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.49(0.55)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.55; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / N-MTL: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, N-MTL, column Mean Acc (%) |
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| Configuration: RGCN / UW | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 64.90(0.39)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.39; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / UW: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, UW, column Mean Acc (%) |
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| Configuration: RGCN / DWA | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.65(0.25)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.25; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / DWA: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, DWA, column Mean Acc (%) |
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| Configuration: Shallow CNN / TS | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.77(0.19)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.19; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / TS: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, TS, column Mean Acc (%) |
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| Configuration: Shallow CNN | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 63.47(0.42)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.42; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, Single-Task, column Mean Acc (%) |
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| Configuration: RGCN | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 65.05(0.21)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.21; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, Single-Task, column Mean Acc (%) |
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| Configuration: Shallow CNN / DWA | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 61.88(0.90)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.9; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceShallow CNN / DWA: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, Shallow CNN, DWA, column Mean Acc (%) |
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| Configuration: RGCN / DTP | Protocol: SugarBase taxonomy · Mean Acc (GlycanML taxonomy prediction) Dataset: SugarBase taxonomy · Mean Acc | 64.15(0.25)% mean accuracy across eight taxonomy tasks percent · higher Uncertainty: type: standard_deviation; value: 0.25; n: 3; unit: same_as_metric Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRGCN / DTP: SugarBase taxonomy · Mean Acc Fixed backbone; compare adaptation strategies, not standalone foundation models. SugarBase taxonomy: motif-frequency K-means cluster allocation 8:1:1. Aggregation: Not reported GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning · Table 4, RGCN, DTP, column Mean Acc (%) |
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