| Configuration: Baseline CNN (PyTorch) | Task: Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-ACCURACY: demo_coding_vs_intergenomic_seqs, Accuracy Dataset subset: demo_coding_vs_intergenomic_seqs (Genomic Benchmarks split) | 87.6% accuracy percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBaseline CNN (PyTorch) on Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-ACCURACY: demo_coding_vs_intergenomic_seqs, Accuracy The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Aggregation: Not reported Genomic benchmarks: a collection of datasets for genomic sequence classification · Table 2, row(demo_coding_vs_intergenomic_seqs), column(Baseline CNN (PyTorch) Accuracy) |
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| Configuration: Baseline CNN (PyTorch) | Task: Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-F1: demo_coding_vs_intergenomic_seqs, F1 score Dataset subset: demo_coding_vs_intergenomic_seqs (Genomic Benchmarks split) | 86.8% f1 percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBaseline CNN (PyTorch) on Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-F1: demo_coding_vs_intergenomic_seqs, F1 score The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Aggregation: Not reported Genomic benchmarks: a collection of datasets for genomic sequence classification · Table 2, row(demo_coding_vs_intergenomic_seqs), column(Baseline CNN (PyTorch) F1 score) |
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| Configuration: Baseline CNN (TensorFlow) | Task: Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-ACCURACY: demo_coding_vs_intergenomic_seqs, Accuracy Dataset subset: demo_coding_vs_intergenomic_seqs (Genomic Benchmarks split) | 89.6% accuracy percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBaseline CNN (TensorFlow) on Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-ACCURACY: demo_coding_vs_intergenomic_seqs, Accuracy The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Aggregation: Not reported Genomic benchmarks: a collection of datasets for genomic sequence classification · Table 2, row(demo_coding_vs_intergenomic_seqs), column(Baseline CNN (TensorFlow) Accuracy) |
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| Configuration: Baseline CNN (TensorFlow) | Task: Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-F1: demo_coding_vs_intergenomic_seqs, F1 score Dataset subset: demo_coding_vs_intergenomic_seqs (Genomic Benchmarks split) | 89.4% f1 percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBaseline CNN (TensorFlow) on Genomic Benchmarks DEMO-CODING-VS-INTERGENOMIC-SEQS-F1: demo_coding_vs_intergenomic_seqs, F1 score The paper's own three-layer convolutional baseline, trained on each dataset's training split and scored on its test split. Architecture is in Table 1. Aggregation: Not reported Genomic benchmarks: a collection of datasets for genomic sequence classification · Table 2, row(demo_coding_vs_intergenomic_seqs), column(Baseline CNN (TensorFlow) F1 score) |
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