{"id":"W4393676596","doi":"10.5281/zenodo.3702149","title":"Data for the paper \"Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study\".","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Motif (music); Benchmarking; Transcription factor; Computational biology; Sequence motif; Data science; Computer science; Biology; Genetics; Business; Gene; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002078805,0.002198332,0.001708284,0.002186748,0.0008776644,0.00203268,0.003551238,0.002892454,0.06912857],"category_scores_gemma":[0.007966911,0.0005393004,0.001486512,0.003824373,0.0006154551,0.001186496,0.002126593,0.002272626,0.05718656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001793641,"about_ca_system_score_gemma":0.003103716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159008,"about_ca_topic_score_gemma":0.03588041,"domain_scores_codex":[0.998013,0.0003893039,0.0002038281,0.0005601909,0.0006015746,0.0002321016],"domain_scores_gemma":[0.9971693,0.001061184,0.0002732237,0.0005461351,0.0005498081,0.0004003868],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001599536,0.00004393291,0.0006801254,0.00115266,0.00006133049,0.00003319945,0.00001650299,0.0005541015,0.0003077326,0.0007152446,0.9941896,0.002085541],"study_design_scores_gemma":[0.0006145174,0.00003627137,0.004705811,0.0004396724,0.0000953685,0.0001344819,0.00005282347,0.0008391784,0.0008489157,0.002769998,0.9894208,0.0000421758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002316273,0.0001727999,0.0001327585,0.0001163314,0.00004257197,0.00001320199,0.9980502,0.000375274,0.0008651983],"genre_scores_gemma":[0.0005409114,0.00005317854,0.0003104773,0.0001060041,0.000005196561,0.00004341801,0.9985129,0.00006412171,0.0003637613],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9979212,"threshold_uncertainty_score":0.2312581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0698976515017638,"score_gpt":0.2729705791951329,"score_spread":0.2030729276933691,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}