{"id":"W6902344285","doi":"10.6084/m9.figshare.29083827","title":"Additional file 1 of Comparison of the distribution of the dental hygienist workforce and population in Ontario: a geospatial analysis","year":2025,"lang":"en","type":"article","venue":"Open MIND","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Geospatial analysis; Workforce; Population; Distribution (mathematics); Work (physics); Geocoding","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001020977,0.0005129745,0.0006961367,0.002643083,0.001460951,0.001171712,0.00131145,0.0005505311,0.6392477],"category_scores_gemma":[0.01998087,0.000408595,0.0007830801,0.007103619,0.0003275899,0.0008025871,0.0008743444,0.0004846774,0.03811291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004758252,"about_ca_system_score_gemma":0.008435,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6379024,"about_ca_topic_score_gemma":0.7281199,"domain_scores_codex":[0.9992484,0.00008500055,0.0001134846,0.0001591913,0.0002469654,0.000146858],"domain_scores_gemma":[0.9868666,0.005973909,0.001048345,0.0009444125,0.004562108,0.0006046318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000173213,0.00006805616,0.0170559,0.001300056,0.00006096333,0.00007724913,0.0002893986,0.0004125216,0.0001121205,0.0006913426,0.9727479,0.007011238],"study_design_scores_gemma":[0.001356547,0.0001280698,0.3077282,0.001834418,0.0002728781,0.0003781166,0.002608736,0.001728716,0.0004351751,0.002729022,0.6806877,0.0001124778],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0007320568,0.000006895464,0.0001067377,0.00004331805,0.000009832025,0.00004705449,0.9979305,0.0000512435,0.001072466],"genre_scores_gemma":[0.02831675,0.0001005242,0.002833721,0.0001453588,0.00004207556,0.001038515,0.9553819,0.0003175426,0.01182367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6392477,"threshold_uncertainty_score":0.7284602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04384191765028105,"score_gpt":0.4159267836732464,"score_spread":0.3720848660229654,"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."}}