{"id":"W7132736105","doi":"","title":"Exploiting Shrinkage Approach in Analysing Gene Expression Data","year":2011,"lang":"en","type":"article","venue":"ASEP","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Principal (computer security); Expression (computer science); Principal component analysis; Gene expression; Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001979306,0.00008588294,0.00008020127,0.00005763971,0.00004351593,0.00001223345,0.0003322531,0.00007857838,0.00003691379],"category_scores_gemma":[0.00002906888,0.00007943203,0.00002612527,0.0001157149,0.00002064093,0.000009038593,0.0002406191,0.00006234702,0.000006523054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000727188,"about_ca_system_score_gemma":0.00002626748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002278329,"about_ca_topic_score_gemma":0.00000651814,"domain_scores_codex":[0.9991359,0.00005654554,0.0001597622,0.000412745,0.000087403,0.0001476511],"domain_scores_gemma":[0.9990727,0.00000251544,0.00006658235,0.0007901939,0.00001907126,0.00004895107],"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":[0.00002228021,0.00006609331,0.006113505,0.000005940172,0.000006150112,0.000001801798,0.0001257609,0.0000153087,0.9884711,0.00001496155,0.001119046,0.004038087],"study_design_scores_gemma":[0.0003362757,0.00002412863,0.01037191,0.00001796986,0.000008430533,0.000003970593,0.0004970068,0.0007679986,0.9828302,0.00003816673,0.004948183,0.0001557828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466888,0.0005995543,0.03865796,0.00001939191,0.00008334834,0.0001153458,0.00001196183,0.00001755919,0.01380611],"genre_scores_gemma":[0.9858387,0.00007354445,0.01317024,0.0000915826,0.0001068112,0.0000185845,0.0005134509,0.00001314866,0.0001740142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03914986,"threshold_uncertainty_score":0.3239144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09816696751920863,"score_gpt":0.291923781895028,"score_spread":0.1937568143758194,"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."}}