{"id":"W4237072225","doi":"10.4212/cjhp.v71i1.1734","title":"scph47","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Hospital Pharmacy","topic":"14-3-3 protein interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001848455,0.0000757346,0.00006463529,0.00005184378,0.0002235707,0.00005307841,0.0003535717,0.0000256291,0.0003154824],"category_scores_gemma":[0.0001251477,0.00005527598,0.00008765254,0.00006531584,0.0002187682,0.000008954961,0.0000197827,0.000159795,0.00008141291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003964346,"about_ca_system_score_gemma":0.000659896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002752574,"about_ca_topic_score_gemma":0.01192525,"domain_scores_codex":[0.9994494,0.00003626896,0.0001617378,0.00007442003,0.00008362057,0.0001946006],"domain_scores_gemma":[0.999148,0.000006239585,0.0001181781,0.0001637832,0.0003006035,0.0002631731],"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":[0.000191878,0.0001004636,0.01570476,0.00001022787,0.0006499721,0.0001780864,0.001349655,0.00003815027,0.2548581,0.000852271,0.7046568,0.02140964],"study_design_scores_gemma":[0.0004244948,0.000626888,0.001280026,0.00001404368,0.00002819661,0.0002110663,0.00007753351,0.000007971403,0.2014887,0.0002830074,0.7954414,0.0001167257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866053,0.0007289919,0.0001136713,0.005062856,0.001713497,0.0000921449,0.00001118274,0.000001886243,0.005670407],"genre_scores_gemma":[0.9963989,0.00002149551,0.0001434201,0.0007645099,0.001882493,0.000001903345,0.000002190797,0.00001354837,0.0007715549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09078456,"threshold_uncertainty_score":0.6654568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01258555584216019,"score_gpt":0.2874405201831008,"score_spread":0.2748549643409406,"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."}}