{"id":"W3047901579","doi":"10.3390/cancers12082222","title":"Modeling the Diversity of Epithelial Ovarian Cancer through Ten Novel Well Characterized Cell Lines Covering Multiple Subtypes of the Disease","year":2020,"lang":"en","type":"article","venue":"Cancers","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Institut Du Cancer de Montréal; Université de Montréal; Canadian Institutes of Health Research; Ovarian Cancer Canada","keywords":"Ovarian cancer; Context (archaeology); Disease; Cancer research; Cell culture; Serous carcinoma; Serous fluid; Malignancy; Cancer; In vivo; Biology; Biomarker; Medicine; Pathology; Internal medicine; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003892052,0.0003200507,0.0003646726,0.000426081,0.0002238992,0.0006179832,0.0003696259,0.0003929941,0.0005228227],"category_scores_gemma":[0.0004268436,0.0001506481,0.0004803472,0.0004874408,0.0002270694,0.0002318875,0.0003894115,0.0005563179,0.0001674689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004229169,"about_ca_system_score_gemma":0.0005259246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004336982,"about_ca_topic_score_gemma":0.0062232,"domain_scores_codex":[0.9997473,0.00005088834,0.00003039766,0.00004734714,0.00008258913,0.00004139316],"domain_scores_gemma":[0.9997447,0.00006998864,0.00004420451,0.00005105766,0.00005737109,0.00003267086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007749659,0.0006389193,0.05522662,0.0004305662,0.0001411096,0.0009740067,0.0006002352,0.1020578,0.8063165,0.005949868,0.001424227,0.02546526],"study_design_scores_gemma":[0.0001972317,0.002713719,0.03829927,0.00008814643,0.000333634,0.002413807,0.001195049,0.3181531,0.5951253,0.002916847,0.03845669,0.0001071411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96794,0.001001015,0.02635184,0.0001509828,0.00003260978,0.0001729948,0.001763799,0.00009858397,0.002488229],"genre_scores_gemma":[0.9681996,0.001299798,0.02497802,0.00008688623,0.000007010764,0.0002312679,0.003455148,0.00002747292,0.001714733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004336982,"threshold_uncertainty_score":0.008623481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03937848391913478,"score_gpt":0.254564843523415,"score_spread":0.2151863596042802,"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."}}