{"id":"W4307036673","doi":"10.1093/nar/gkac909","title":"The Chemical Probes Portal: an expert review-based public resource to empower chemical probe assessment, selection and use","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"Cancer Prevention and Research Institute of Texas; Institute of Cancer Research; Wellcome Trust; Ontario Institute for Cancer Research; Janssen Biotech; Ontario Genomics Institute; Structural Genomics Consortium; Merck KGaA; Pfizer; Takeda Pharmaceuticals U.S.A.; Chordoma Foundation; Deutsches Krebsforschungszentrum","keywords":"Biology; Selection (genetic algorithm); Resource (disambiguation); Computational biology; Computer science; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003434059,0.0001947371,0.0001971076,0.0001371082,0.0007752364,0.0002982828,0.0008495354,0.0001614702,0.0001688882],"category_scores_gemma":[0.001599764,0.000147085,0.00008218822,0.0006003886,0.0004757061,0.0000193375,0.001219568,0.0008145933,0.00001040088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106218,"about_ca_system_score_gemma":0.0005487885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002699847,"about_ca_topic_score_gemma":0.00001792112,"domain_scores_codex":[0.9959214,0.0005482644,0.0004095884,0.0005965985,0.001620561,0.0009036012],"domain_scores_gemma":[0.9980915,0.0001165138,0.00006174221,0.0006746604,0.0004645489,0.0005909934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002424477,0.0003911221,0.001635868,0.0001617355,0.00004597315,0.000006025912,0.0001313812,0.000001505889,0.8282419,0.0001553435,0.14,0.02898664],"study_design_scores_gemma":[0.0005262719,0.001391385,0.0006412106,0.00004752725,0.000006140255,0.00003672128,0.0005470002,0.00137676,0.06893957,0.00005102014,0.9261529,0.0002834812],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738365,0.001919393,0.0007474092,0.01890019,0.000114085,0.002403341,0.00005433008,0.00006405085,0.001960636],"genre_scores_gemma":[0.9887415,0.001486714,0.004376682,0.002531994,0.0003505428,0.0008084121,0.0004419361,0.00006513252,0.001197143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7861529,"threshold_uncertainty_score":0.5997951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04640446147400395,"score_gpt":0.378704125134632,"score_spread":0.3322996636606281,"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."}}