{"id":"W2910179375","doi":"10.12927/hcpol.2018.25692","title":"Illuminating the Consequences of Policy Change","year":2018,"lang":"fr","type":"editorial","venue":"Healthcare policy","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unintended consequences; Value (mathematics); Policy analysis; Health policy; Public economics; Political science; Actuarial science; Economics; Computer science; Economic growth; Public administration; Health care","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003507637,0.0008567043,0.001933771,0.001908619,0.0009417873,0.0001534788,0.001686306,0.001569084,0.0002997223],"category_scores_gemma":[0.009479729,0.0008755674,0.000568009,0.002310094,0.002415321,0.0003338002,0.0006858058,0.001517237,0.001000665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002610992,"about_ca_system_score_gemma":0.00402997,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7597641,"about_ca_topic_score_gemma":0.02349655,"domain_scores_codex":[0.9922818,0.000605986,0.003152056,0.001305073,0.0004040917,0.002250985],"domain_scores_gemma":[0.991818,0.001598291,0.003539915,0.001784509,0.0006923979,0.0005669518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003097874,0.00009469675,0.0004744255,0.003855031,0.0001514568,0.000008049581,0.01176524,0.000001045647,9.719613e-7,0.7847259,0.1600337,0.03885847],"study_design_scores_gemma":[0.0004797302,0.0006238813,0.0009599624,0.0009845349,0.0000267674,0.00001148498,0.0009419273,0.00007079946,0.00003262829,0.04049836,0.9547121,0.0006578427],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.0008738859,0.01980664,0.0000644892,0.6703427,0.2824572,0.002272519,0.007188381,0.00008541541,0.01690873],"genre_scores_gemma":[0.176723,0.02586232,0.0003754972,0.01427213,0.7730767,0.0005662807,0.0002431524,0.0001758652,0.008705059],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.7946784,"threshold_uncertainty_score":0.9997772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1085139795883177,"score_gpt":0.3582315544860702,"score_spread":0.2497175748977525,"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."}}