{"id":"W2754902956","doi":"10.1177/1176935117730016","title":"Gene-Set Reduction for Analysis of Major and Minor Gleason Scores Based on Differential Gene-Set Expressions and Biological Pathways in Prostate Cancer","year":2017,"lang":"en","type":"article","venue":"Cancer Informatics","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Prostate cancer; Medicine; Prostate; Microarray; Oncology; Cancer; Microarray analysis techniques; Internal medicine; Bioinformatics; Gene; Biology; Gene expression; Genetics","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":[0.0009716196,0.0005436653,0.0008868568,0.00159106,0.0004876665,0.0006761138,0.0004572832,0.0002665953,0.002314731],"category_scores_gemma":[0.002298751,0.000193472,0.001319204,0.001778372,0.0004018854,0.0002849615,0.0005168107,0.0007865937,0.0004444243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005595224,"about_ca_system_score_gemma":0.0008300162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00150625,"about_ca_topic_score_gemma":0.002201511,"domain_scores_codex":[0.9992593,0.0001901701,0.00004679459,0.0001546494,0.0002462139,0.0001028602],"domain_scores_gemma":[0.9994075,0.0003450345,0.00006134394,0.00007860359,0.00007570112,0.00003177347],"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":[0.002065858,0.001016051,0.05338969,0.0007459749,0.0008886756,0.000308226,0.0005216025,0.02324031,0.5546665,0.005886312,0.004408841,0.3528621],"study_design_scores_gemma":[0.0002048023,0.001877461,0.3854932,0.00008224127,0.0007278023,0.0007967001,0.0008014497,0.3481677,0.2306733,0.01463878,0.01633017,0.0002063927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7577845,0.0009667258,0.228064,0.0004553046,0.000142079,0.0004525859,0.00637162,0.002812281,0.002950797],"genre_scores_gemma":[0.7315245,0.0003540534,0.2538837,0.0001594642,0.00004547187,0.001082755,0.01046597,0.0002627371,0.002221391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002314731,"threshold_uncertainty_score":0.007743478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1056850849525111,"score_gpt":0.3781212343743655,"score_spread":0.2724361494218543,"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."}}