{"id":"W2066613669","doi":"10.1007/s00439-014-1440-6","title":"Application of quantile regression to recent genetic and -omic studies","year":2014,"lang":"en","type":"review","venue":"Human Genetics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"Mitacs","keywords":"Quantile regression; Biology; Regression; Human genetics; Quantile; Regression analysis; Computational biology; Computer science; Econometrics; Statistics; Data mining; Machine learning; Genetics; Mathematics; Gene","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":[0.000145614,0.0002952667,0.0007000112,0.0001244734,0.00008223018,0.00001393848,0.0002649444,0.0002727219,0.000006817965],"category_scores_gemma":[0.00003902158,0.0002417727,0.00011954,0.0001338912,0.00008547155,7.672579e-7,0.0002398962,0.00008638476,0.00001260068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002527698,"about_ca_system_score_gemma":0.00007062813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001575309,"about_ca_topic_score_gemma":0.000008085958,"domain_scores_codex":[0.9984224,0.000128197,0.0005560638,0.0005724667,0.0001528195,0.0001680772],"domain_scores_gemma":[0.9985477,0.00001306486,0.0004274019,0.0007549764,0.000155522,0.0001013604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006459465,0.00002865779,0.00002672566,0.003300377,0.00007064138,1.531671e-7,0.00004090851,0.000008665535,0.01771487,0.00004391003,0.007837295,0.9709213],"study_design_scores_gemma":[0.0001175683,0.000188546,0.00009062415,0.001121758,0.0001753877,0.00000496456,0.00002560842,0.000006809306,0.002962167,0.00004285684,0.9950125,0.0002512523],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001556095,0.996052,0.001462666,0.00002209076,0.0001354704,0.0006495105,0.0000140219,0.000008862347,0.00009928108],"genre_scores_gemma":[0.001484449,0.9963834,0.0009998935,0.00006072131,0.0002627253,0.0002012694,0.0001576723,0.00005135176,0.0003984777],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9871752,"threshold_uncertainty_score":0.9859203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0769709638510358,"score_gpt":0.4035201779953602,"score_spread":0.3265492141443244,"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."}}