{"id":"W2169188167","doi":"10.1136/jech.2010.110437","title":"Learning lessons from past mistakes: how can Health in All Policies fulfil its promises?","year":2010,"lang":"en","type":"article","venue":"Journal of Epidemiology & Community Health","topic":"Public Health Policies and Education","field":"Health Professions","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health promotion; Charter; Public health; Health policy; Medicine; Public relations; Empowerment; Population health; Health education; Social determinants of health; Health equity; Citizen journalism; Equity (law); International health; Economic growth; Political science; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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","sts","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04000368,0.0003566121,0.002048531,0.000638098,0.002804483,0.00001861296,0.001006992,0.0006241092,0.0001718565],"category_scores_gemma":[0.0249894,0.0003065971,0.0001930491,0.0004851831,0.000243441,0.0002915311,0.0001730267,0.01547694,0.00002549595],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001818304,"about_ca_system_score_gemma":0.01284602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2722506,"about_ca_topic_score_gemma":0.2633134,"domain_scores_codex":[0.9644746,0.02922064,0.003449028,0.0002974853,0.0002454319,0.002312849],"domain_scores_gemma":[0.9725764,0.01818942,0.00571797,0.001044643,0.0006276324,0.001843869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001752211,0.0007944144,0.5669014,0.001019549,0.0001037181,0.000002413243,0.1233082,0.00009631883,0.0001700889,0.009056083,0.2821894,0.01618318],"study_design_scores_gemma":[0.001066544,0.000743761,0.4983399,0.0006242815,0.000008372792,0.00002165978,0.04012885,0.00008483786,9.18515e-7,0.002276921,0.4565381,0.000165863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.492123,0.0007850304,0.00008648849,0.5038444,0.001719335,0.0004815832,0.00006985958,0.00003556872,0.0008546402],"genre_scores_gemma":[0.8682998,0.003980794,0.003062819,0.1214556,0.002432067,0.00005127691,0.0001852344,0.00005645895,0.0004759113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3823889,"threshold_uncertainty_score":0.9999386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3434014219248198,"score_gpt":0.555965429291876,"score_spread":0.2125640073670562,"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."}}