{"id":"W2342444510","doi":"10.1097/00005650-200009002-00027","title":"Response to Testa: Making Sense of Quality-of-Life Data","year":2000,"lang":"en","type":"letter","venue":"Medical Care","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McMaster University Medical Centre; Health Sciences Centre","funders":"","keywords":"Biostatistics; Clinical epidemiology; Epidemiology; Medicine; Quality of life (healthcare); MEDLINE; Gerontology; Family medicine; Library science; Computer science; Nursing; Political science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01069285,0.0004723582,0.0008013177,0.0005903204,0.002325541,0.002552581,0.001322328,0.02327539,0.01912041],"category_scores_gemma":[0.1042603,0.0003481099,0.000579488,0.000623124,0.001450805,0.002397539,0.001719853,0.01799565,0.007200831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003038979,"about_ca_system_score_gemma":0.001998943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004346136,"about_ca_topic_score_gemma":0.004459584,"domain_scores_codex":[0.9922985,0.004601178,0.0009246719,0.0004967187,0.001132778,0.0005461806],"domain_scores_gemma":[0.9446854,0.04269793,0.002270265,0.001641042,0.006121265,0.002584065],"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":[0.0001494345,0.0000285104,0.003367085,0.00006804348,0.00001483429,0.001943801,0.0005889236,0.000096801,0.0002307959,0.004466946,0.9725619,0.01648287],"study_design_scores_gemma":[0.0003059442,0.0001655262,0.01245914,0.000918519,0.00003531763,0.00581626,0.003940507,0.002923824,0.0005862422,0.02152712,0.9512064,0.0001151086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001144393,0.0001404915,0.0002634384,0.9916735,0.002441654,0.0000364472,0.00008437833,0.00002818522,0.004187524],"genre_scores_gemma":[0.02888012,0.0004889539,0.0009840069,0.9496807,0.006271887,0.0001927614,0.0001225221,0.00005976733,0.01331918],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02327539,"threshold_uncertainty_score":0.06396419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.557765625728083,"score_gpt":0.5057642306746779,"score_spread":0.05200139505340506,"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."}}