{"id":"W2606808455","doi":"10.23889/ijpds.v1i1.79","title":"An Integrated Genomics and Clinical Resource for Data-Driven Health Services Policy and Practice Decisionmaking","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Health care; Medicine; Breast cancer; Biobank; Family medicine; Cancer; Gerontology; Internal medicine; Bioinformatics; Biology","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":[0.05805549,0.001375371,0.002770858,0.01209996,0.001881159,0.01146441,0.006278045,0.002906343,0.07915661],"category_scores_gemma":[0.1522707,0.001572351,0.001916519,0.01579099,0.001082045,0.007683422,0.01201336,0.003484605,0.02621764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006317875,"about_ca_system_score_gemma":0.02405017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01399269,"about_ca_topic_score_gemma":0.01393321,"domain_scores_codex":[0.9626181,0.02358624,0.005338094,0.002868067,0.004450665,0.001138886],"domain_scores_gemma":[0.8146394,0.1021658,0.009062064,0.03744061,0.022332,0.01436005],"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":[0.0006899092,0.0005773171,0.01188625,0.001120115,0.0004321588,0.0003784792,0.0008937911,0.009707282,0.0005911877,0.03630004,0.5937391,0.3436844],"study_design_scores_gemma":[0.0008742347,0.0002250507,0.009691835,0.002813746,0.0002755139,0.0002160105,0.002354494,0.04255133,0.001562851,0.1378574,0.8012823,0.0002953276],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01114653,0.003721092,0.3060144,0.1536279,0.002186229,0.01110172,0.3128178,0.04363748,0.1557469],"genre_scores_gemma":[0.09390326,0.003492703,0.6560397,0.01178487,0.001808664,0.01023984,0.2059474,0.004975764,0.01180777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07915661,"threshold_uncertainty_score":0.3070304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1352735907040793,"score_gpt":0.5334549334104957,"score_spread":0.3981813427064163,"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."}}