{"id":"W3096856821","doi":"10.1016/j.patter.2020.100138","title":"A Blueprint for Identifying Phenotypes and Drug Targets in Complex Disorders with Empirical Dynamics","year":2020,"lang":"en","type":"article","venue":"Patterns","topic":"Blood properties and coagulation","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Blueprint; Phenotype; Observational study; Intervention (counseling); Computational biology; Data science; Computer science; Cognitive psychology; Psychology; Neuroscience; Cognitive science; Biology; Medicine; Genetics; Psychiatry; Engineering; Pathology; Gene","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":[0.00003508684,0.00006416118,0.0001253931,0.00001870242,0.00002660277,0.00001388636,0.00002552314,0.00001810141,0.00002579508],"category_scores_gemma":[0.00001143015,0.00004847728,0.000018191,0.0000421576,0.00001590114,0.00003234683,0.00002769026,0.00006308502,0.000001965944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001535548,"about_ca_system_score_gemma":0.000009838108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001655248,"about_ca_topic_score_gemma":0.001408284,"domain_scores_codex":[0.9995678,0.00001008972,0.00009691286,0.0001496745,0.00007094717,0.0001045703],"domain_scores_gemma":[0.9998359,0.0000158582,0.00002188813,0.00005630241,0.0000148537,0.00005517747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002237061,0.00004518845,0.9828962,0.0002600949,0.00002278504,0.000002928611,0.003003995,0.00004691256,0.0001857344,0.0000523933,0.00008086407,0.0131792],"study_design_scores_gemma":[0.001741212,0.0001872375,0.8892667,0.00006981479,0.0000453744,0.000003129769,0.001216043,0.1062949,0.0001342343,0.0001823208,0.00075192,0.0001070721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959465,0.00008892061,0.02609513,0.01392392,0.00001287996,0.000307769,0.000008394105,0.00002193079,0.00007601563],"genre_scores_gemma":[0.9974735,0.00001382729,0.001023628,0.001355191,0.00004022857,0.00002067615,0.00004272735,0.00001253634,0.00001772112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.106248,"threshold_uncertainty_score":0.1976846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06547593480665075,"score_gpt":0.307832588936986,"score_spread":0.2423566541303352,"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."}}