{"id":"W2081436300","doi":"10.1158/1078-0432.ovca13-ia20","title":"Abstract IA20: Analyzing the cellular basis for heterogeneity in serous ovarian carcinoma","year":2013,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research","funders":"","keywords":"Serous fluid; Ovarian cancer; Cancer research; Population; Flow cytometry; Malignancy; Ovarian carcinoma; Medicine; Cancer stem cell; Cancer; Targeted therapy; Oncology; Biology; Pathology; Immunology; Internal medicine","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":[0.0002155062,0.0001191813,0.0001453752,0.0005953006,0.0001543363,0.000353783,0.0001462796,0.0001712866,0.001058887],"category_scores_gemma":[0.000205514,0.00006355401,0.0001162548,0.0003666993,0.0001631166,0.0001402246,0.000195951,0.0002111231,0.0001977955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002608377,"about_ca_system_score_gemma":0.0001296578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007928062,"about_ca_topic_score_gemma":0.0005947035,"domain_scores_codex":[0.9999131,0.00001180961,0.00000672441,0.00002079589,0.00002408791,0.00002352594],"domain_scores_gemma":[0.9998595,0.00003310166,0.00002475151,0.00001604262,0.00002659519,0.00004004511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002114099,0.00003935033,0.01910044,0.00002725845,0.00001206213,0.0001222678,0.00004496336,0.0001613373,0.9773086,0.0001310033,0.00007024233,0.002771006],"study_design_scores_gemma":[0.00003463242,0.0009719996,0.4147622,0.00001436572,0.00007022666,0.002036076,0.0004216836,0.009304959,0.565898,0.000336948,0.006134887,0.00001410453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977082,0.0003382582,0.00111251,0.0000183863,0.000003641277,0.00002271732,0.0002143505,0.00002076068,0.0005611675],"genre_scores_gemma":[0.9981667,0.0001467204,0.0007938312,0.00001696511,0.000003333049,0.00001893904,0.0004937784,0.000008351067,0.0003514129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001058887,"threshold_uncertainty_score":0.003542304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1372811574916157,"score_gpt":0.4445392617858377,"score_spread":0.3072581042942221,"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."}}