{"id":"W2138453085","doi":"10.1093/bioinformatics/bts430","title":"Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data","year":2012,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Institutes of Health; Michael Smith Health Research BC","keywords":"Computer science; License; Gemma; Profiling (computer programming); Plug-in; Software; World Wide Web; Data science; Database; Information retrieval; Biology; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004937082,0.00007659453,0.0001767499,0.0000495114,0.00008703265,0.00001934156,0.0004421673,0.00006204421,0.00000977264],"category_scores_gemma":[0.0001960412,0.00004513747,0.0001139794,0.0001241228,0.00003504044,0.00001505858,0.0004853045,0.00003172232,4.845423e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002688576,"about_ca_system_score_gemma":0.00001301956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001529993,"about_ca_topic_score_gemma":0.00000121737,"domain_scores_codex":[0.999406,0.00001351902,0.0002453855,0.000114754,0.00009991208,0.0001204496],"domain_scores_gemma":[0.9985304,0.00003371409,0.0001844905,0.001167592,0.00004245911,0.00004134061],"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":[0.0004260734,0.0002780215,0.01088645,0.0007389361,0.07809789,8.956393e-8,0.004678363,0.001927702,0.7900794,0.002379002,0.1024351,0.008073034],"study_design_scores_gemma":[0.0005911769,0.00008927286,0.001658189,0.000008854529,0.08694382,0.000003296955,0.002706317,0.1115918,0.5423403,0.00004905181,0.2536362,0.0003817529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3425242,0.0406789,0.6030632,0.002460765,0.000410055,0.003648343,0.001670579,0.00007762246,0.005466345],"genre_scores_gemma":[0.9616688,0.0001857039,0.03632188,0.0002723377,0.00009573508,0.00008319569,0.0008471676,0.00001323473,0.0005119059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6191446,"threshold_uncertainty_score":0.1840653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1543445386825175,"score_gpt":0.3402158842362292,"score_spread":0.1858713455537117,"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."}}