{"id":"W2124146356","doi":"10.1158/0008-5472.can-07-2580","title":"Multiple Alternative Splicing Markers for Ovarian Cancer","year":2008,"lang":"en","type":"article","venue":"Cancer Research","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":155,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Ovarian cancer; RNA splicing; Alternative splicing; Biology; Gene expression profiling; Cancer; Computational biology; Gene; Microarray; Serous ovarian cancer; Cancer research; Splicing factor; Bioinformatics; Gene expression; Genetics; Exon; RNA","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":[0.0006095001,0.000166537,0.0002376335,0.001520725,0.0001925197,0.0004781812,0.0001348619,0.0002588663,0.001129487],"category_scores_gemma":[0.0008865889,0.00008689135,0.0001688239,0.0006807992,0.0001956402,0.000225942,0.000338931,0.0004153754,0.0002738444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001823,"about_ca_system_score_gemma":0.0001691349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002367077,"about_ca_topic_score_gemma":0.0005446377,"domain_scores_codex":[0.9997454,0.00006078358,0.00002538914,0.00005008945,0.00009869997,0.00001967072],"domain_scores_gemma":[0.9995363,0.0001582163,0.0001587462,0.00002831813,0.00007059964,0.00004784931],"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":[0.0007552009,0.0001325604,0.2205916,0.0001897542,0.00008143493,0.0006895344,0.0001420455,0.0009702142,0.6674838,0.0009423479,0.0008751141,0.1071464],"study_design_scores_gemma":[0.00006056648,0.001064332,0.6535853,0.00007346969,0.0002486171,0.01085646,0.0002708516,0.02224308,0.287912,0.004838794,0.01878652,0.00006013005],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749691,0.003578034,0.01706291,0.0002749616,0.00004561123,0.00007841091,0.0008063741,0.0003502684,0.002834436],"genre_scores_gemma":[0.9743069,0.0008192691,0.02304729,0.00007615282,0.00002771361,0.00004498466,0.0008579334,0.00001998049,0.000799667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001520725,"threshold_uncertainty_score":0.003778458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08250446163454854,"score_gpt":0.4108390209229895,"score_spread":0.3283345592884409,"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."}}