{"id":"W2364148038","doi":"10.1039/c6md00065g","title":"Open PHACTS computational protocols for <i>in silico</i> target validation of cellular phenotypic screens: knowing the knowns","year":2016,"lang":"en","type":"article","venue":"MedChemComm","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"De Beers (Canada)","funders":"Instituto de Salud Carlos III; Horizon 2020 Framework Programme; Innovative Medicines Initiative; European Federation of Pharmaceutical Industries and Associations","keywords":"In silico; Phenotype; Computer science; Computational biology; Biology; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.003609974,0.001972667,0.001470019,0.001374671,0.001426361,0.00313469,0.005749426,0.001729428,0.04734865],"category_scores_gemma":[0.006851463,0.001560612,0.002946122,0.001844605,0.001028218,0.002429855,0.002898016,0.003793944,0.01690305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001981322,"about_ca_system_score_gemma":0.004443411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006135385,"about_ca_topic_score_gemma":0.00902575,"domain_scores_codex":[0.9990919,0.0002072115,0.0001350583,0.0001597958,0.0002967942,0.000109262],"domain_scores_gemma":[0.9971892,0.001299839,0.0001350672,0.0007755059,0.0004658558,0.0001344824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002876082,0.0005631395,0.004616791,0.004388279,0.001053982,0.001030964,0.0009441143,0.1233148,0.02690214,0.1095144,0.5470471,0.1777482],"study_design_scores_gemma":[0.001031666,0.0001416281,0.001479184,0.0002953051,0.0002145299,0.0004060938,0.0002181862,0.5078041,0.05781662,0.1013197,0.3289197,0.0003532649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.006526542,0.0002270819,0.7294295,0.0005612233,0.0002868149,0.0006447719,0.04392981,0.2052656,0.01312868],"genre_scores_gemma":[0.04805104,0.0007104626,0.753258,0.000833866,0.00007459774,0.005116814,0.1295092,0.05315077,0.009295335],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.04734865,"threshold_uncertainty_score":0.158397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336625622666653,"score_gpt":0.3190598331509922,"score_spread":0.2956935769243257,"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."}}