{"id":"W2885666535","doi":"10.1093/heapro/day047","title":"Adapting a health equity tool to meet professional needs (Québec, Canada)","year":2018,"lang":"en","type":"article","venue":"Health Promotion International","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Santé Montérégie; Université Laval","funders":"","keywords":"Equity (law); Health equity; Public relations; Knowledge management; Business; Adaptation (eye); Population; Health literacy; Psychology; Health care; Political science; Medicine; Nursing; Public health; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007153661,0.0002771256,0.000435583,0.0005205809,0.003239321,0.00003556923,0.0007375409,0.000120805,0.005996488],"category_scores_gemma":[0.002561765,0.0002694273,0.00005241918,0.0009615271,0.0001050134,0.0003888724,0.0006078603,0.0005552633,0.000665894],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.008148137,"about_ca_system_score_gemma":0.05213474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5282375,"about_ca_topic_score_gemma":0.9128282,"domain_scores_codex":[0.99165,0.001616869,0.002279683,0.0006073074,0.00208866,0.001757452],"domain_scores_gemma":[0.9951189,0.0006976314,0.001245835,0.0004343031,0.001294017,0.00120927],"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":[0.00006784518,0.0001004503,0.01374018,0.0002719286,0.0000182686,0.000001305821,0.01537092,0.000008594311,0.00004530676,0.01904592,0.9352376,0.01609168],"study_design_scores_gemma":[0.001089616,0.0006321195,0.04509561,0.0005962289,0.000001954191,0.000009328975,0.003112161,0.0009722552,0.00002175882,0.0004746199,0.9477081,0.0002862123],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09827591,0.0000185882,0.01217657,0.8583712,0.01064164,0.003595423,0.0004570224,0.0002690051,0.01619465],"genre_scores_gemma":[0.6959284,0.000007599431,0.005165634,0.2873123,0.002905895,0.0008191287,0.00006433931,0.00004580976,0.007750939],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.5976524,"threshold_uncertainty_score":0.9999758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5183039199251039,"score_gpt":0.6614547510978348,"score_spread":0.1431508311727309,"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."}}