{"id":"W1598911098","doi":"10.1111/j.1553-2712.2012.01386.x","title":"Why Quantile Regression Makes Good Sense for Analyzing Economic Outcomes in Medical Research","year":2012,"lang":"en","type":"letter","venue":"Academic Emergency Medicine","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Family Medicine","funders":"","keywords":"Medicine; Quantile regression; Econometrics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.00992343,0.0005173316,0.001687811,0.002016795,0.0001950128,0.000003110474,0.0008689594,0.002278591,0.005878931],"category_scores_gemma":[0.002504941,0.0004680452,0.0002621813,0.0004805269,0.0002102824,0.0002141266,0.0002768092,0.005242984,0.0006620723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005576088,"about_ca_system_score_gemma":0.0001179663,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01450061,"about_ca_topic_score_gemma":0.0008801455,"domain_scores_codex":[0.9932204,0.0002642845,0.00337314,0.001080093,0.0003477547,0.001714285],"domain_scores_gemma":[0.9968653,0.0009318428,0.0009776409,0.0008075509,0.00006705634,0.0003506553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001444781,0.00002251497,0.04305033,0.000678833,0.00009986313,0.00002632743,0.0005521381,0.000001466655,0.000001236178,0.01909518,0.9359278,0.0005298521],"study_design_scores_gemma":[0.0007203977,0.00009768976,0.001441708,0.0005102638,0.00002481667,0.00000536123,0.0000977342,0.0003577861,0.000002353572,0.01325646,0.9830496,0.0004358523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003761848,0.02567102,0.0002757247,0.9550694,0.006563499,0.001180206,0.0002392297,0.00005820241,0.007180922],"genre_scores_gemma":[0.0334154,0.1457844,0.0002100243,0.7379876,0.04604572,0.001470902,0.001329039,0.000465363,0.03329152],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2170817,"threshold_uncertainty_score":0.9997771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2276073668349216,"score_gpt":0.4467250353594214,"score_spread":0.2191176685244999,"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."}}