{"id":"W4405783080","doi":"10.2196/62939","title":"Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024)","year":2025,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Public health; Population health; Population; Agriculture; Environmental health; Thematic analysis; Medicine; Data science; Geography; Qualitative research; Social science; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.04401506,0.001841819,0.00742079,0.2474699,0.002269916,0.008676642,0.002916985,0.002282284,0.005138236],"category_scores_gemma":[0.1856775,0.001603924,0.005898403,0.2126739,0.002170401,0.009041873,0.006193192,0.001407074,0.0007979482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01169747,"about_ca_system_score_gemma":0.04314968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01675656,"about_ca_topic_score_gemma":0.02832844,"domain_scores_codex":[0.9461762,0.0111943,0.02840121,0.002806191,0.01016251,0.0012596],"domain_scores_gemma":[0.7463843,0.1762141,0.03435772,0.004642717,0.03647432,0.001926776],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000170156,0.00003950502,0.007651682,0.8391768,0.004502975,0.0004605109,0.00267414,0.0004838708,0.0004826343,0.002458461,0.007287459,0.1346117],"study_design_scores_gemma":[0.00009599618,0.0001634444,0.02415687,0.8850663,0.01811795,0.000585171,0.004116001,0.0005232776,0.0005127204,0.001862491,0.06469002,0.000109731],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01551685,0.9442864,0.002615239,0.005043052,0.000760606,0.004035246,0.02194658,0.0001687836,0.00562717],"genre_scores_gemma":[0.05903309,0.9105472,0.01014823,0.001257813,0.0004664102,0.006800267,0.01108479,0.00006334361,0.0005989316],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.955985,"threshold_uncertainty_score":0.2327767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.23661032994561,"score_gpt":0.4178225115411915,"score_spread":0.1812121815955816,"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."}}