{"id":"W2608521041","doi":"10.1177/0272989x17696999","title":"An Approach to Reconciling Competing Ethical Principles in Aggregating Heterogeneous Health Preferences","year":2017,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Social Sciences and Humanities Research Council of Canada; National Institutes of Health","keywords":"Preference; Social choice theory; Set (abstract data type); Social preferences; Psychological intervention; Aggregation problem; Quality (philosophy); Quality of life (healthcare); Psychology; Actuarial science; Management science; Social psychology; Economics; Computer science; Microeconomics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05523021,0.0002316929,0.00121363,0.00037334,0.0009102965,0.0004347784,0.001302805,0.0004299763,0.0002606467],"category_scores_gemma":[0.05660892,0.0002617953,0.00009906817,0.0001384619,0.0001149142,0.0003504711,0.0003211214,0.0009050464,0.00033088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005378915,"about_ca_system_score_gemma":0.0003662528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000621586,"about_ca_topic_score_gemma":0.0009637431,"domain_scores_codex":[0.99215,0.0007295442,0.004883836,0.00104867,0.0004802514,0.0007076887],"domain_scores_gemma":[0.9930699,0.002468858,0.002653235,0.001089119,0.00006122351,0.0006576418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001233967,0.0004986404,0.5174841,0.0009143568,0.0000599467,0.00003511718,0.01952899,0.02105057,0.000002768047,0.08252496,0.0009956144,0.3567815],"study_design_scores_gemma":[0.00164321,0.0003200999,0.179529,0.005088361,0.000003058295,0.00006216519,0.00268205,0.7695464,0.0000041954,0.03110369,0.009058757,0.0009589826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8589275,0.0005862401,0.1142483,0.01965942,0.0007706091,0.0006798846,0.0000294142,0.00007550946,0.005023094],"genre_scores_gemma":[0.8981926,0.00004216444,0.08503504,0.01620592,0.0004088764,0.00006214393,0.000007547579,0.00003107097,0.00001457076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7484959,"threshold_uncertainty_score":0.9999834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5507894761827204,"score_gpt":0.5235710952411564,"score_spread":0.02721838094156404,"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."}}