{"id":"W3155272599","doi":"10.1101/2021.04.11.439248","title":"Experiment level curation identifies high confidence transcriptional regulatory interactions in neurodevelopment","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Department of Psychiatry, Faculty of Medicine, University of British Columbia; National Institutes of Health","keywords":"In silico; Computational biology; Biology; ETS transcription factor family; Transcription factor; Gene; Identification (biology); Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.02213614,0.001882031,0.002659698,0.01898916,0.002626869,0.004748207,0.003135624,0.001674591,0.009694266],"category_scores_gemma":[0.07934412,0.0009524127,0.003246985,0.01482805,0.001678718,0.002229164,0.003763193,0.002048991,0.006053286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002406716,"about_ca_system_score_gemma":0.008902199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004064968,"about_ca_topic_score_gemma":0.01259658,"domain_scores_codex":[0.9774775,0.00513325,0.00496893,0.004801647,0.006807551,0.0008111401],"domain_scores_gemma":[0.8857774,0.06694604,0.009134914,0.01640121,0.02028708,0.001453482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002086347,0.0004683276,0.0921817,0.1156074,0.005220199,0.008580323,0.003086585,0.00907321,0.26719,0.01641717,0.1473205,0.3327684],"study_design_scores_gemma":[0.0003354558,0.0004765506,0.142584,0.01282409,0.006541224,0.004063615,0.001093589,0.02017022,0.1567881,0.01878428,0.6359047,0.0004341586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1315733,0.1020618,0.3755978,0.004533379,0.002778322,0.003534944,0.3029921,0.03163675,0.04529151],"genre_scores_gemma":[0.2550238,0.01875839,0.4081812,0.002423678,0.0007104349,0.004825859,0.2965548,0.005170661,0.008351281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02213614,"threshold_uncertainty_score":0.1170685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02199439032842132,"score_gpt":0.2365958712881281,"score_spread":0.2146014809597068,"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."}}