{"id":"W2111018099","doi":"10.1002/sim.1851","title":"The use of quantile regression in health care research: a case study examining gender differences in the timeliness of thrombolytic therapy","year":2004,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; Women's College Hospital; Toronto General Hospital; University of Toronto","funders":"","keywords":"Quantile regression; Quantile; Thrombolysis; Medicine; Regression analysis; Statistics; Regression; Linear regression; Econometrics; Proportional hazards model; Myocardial infarction; Mathematics; Internal medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04439943,0.0003695114,0.0008780198,0.00155759,0.001792386,0.001522605,0.00101076,0.002403228,0.001732434],"category_scores_gemma":[0.08791648,0.000371715,0.001228697,0.004472656,0.002551103,0.001769941,0.002025679,0.00232585,0.000177392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002622005,"about_ca_system_score_gemma":0.002222313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0146823,"about_ca_topic_score_gemma":0.0125602,"domain_scores_codex":[0.9636979,0.03335483,0.0005571041,0.0005153024,0.001150398,0.0007245209],"domain_scores_gemma":[0.864196,0.1235161,0.005434097,0.003248068,0.002692857,0.0009128419],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001700102,0.001731717,0.5008596,0.0007216501,0.0005844374,0.02004336,0.02708735,0.03466838,0.001271562,0.1572168,0.01365706,0.240458],"study_design_scores_gemma":[0.0006817013,0.004316731,0.338239,0.001410081,0.0009123991,0.02052285,0.06132329,0.3216725,0.004549584,0.1954153,0.05036924,0.0005873417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8368339,0.008103047,0.1117565,0.02754915,0.0002302947,0.0004033627,0.0004820337,0.00009279952,0.01454889],"genre_scores_gemma":[0.965983,0.002395876,0.02999599,0.0006233815,0.00008524183,0.0001779071,0.0000606895,0.00002734504,0.0006505843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9556006,"threshold_uncertainty_score":0.2348094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8464695569015244,"score_gpt":0.5826981290513751,"score_spread":0.2637714278501493,"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."}}