{"id":"W2076472002","doi":"10.1186/1478-4491-11-65","title":"The value of survival analyses for evidence-based rural medical workforce planning","year":2013,"lang":"en","type":"article","venue":"Human Resources for Health","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Primary Health Care Research Institute, Australian National University; Australian Government","keywords":"Workforce; Health services research; Medicine; Workforce planning; Turnover; Public health; Health administration; Rural health; Rural area; Health care; Family medicine; Geography; Nursing; Gerontology; Economic growth; Management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3754917,0.001514554,0.003078946,0.01401121,0.00107466,0.007174365,0.004057258,0.003429211,0.009538816],"category_scores_gemma":[0.6516487,0.0009750976,0.008086475,0.009104434,0.005536577,0.009164359,0.005978429,0.008377304,0.001031837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003285541,"about_ca_system_score_gemma":0.01196547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004112682,"about_ca_topic_score_gemma":0.005260952,"domain_scores_codex":[0.661437,0.2845977,0.02285973,0.007801443,0.02190086,0.001403349],"domain_scores_gemma":[0.07109837,0.8662648,0.02370786,0.02122879,0.01598464,0.00171557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00280803,0.0005949567,0.2302883,0.0452156,0.02694826,0.0005161015,0.00285777,0.02031412,0.0005063388,0.06728474,0.03625928,0.5664065],"study_design_scores_gemma":[0.001375659,0.004895589,0.1912736,0.144997,0.02001466,0.001105106,0.00594784,0.08558749,0.001372307,0.3806952,0.1621714,0.0005642017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07441304,0.2258443,0.5181839,0.1261957,0.009433482,0.004236063,0.01714203,0.001152429,0.02339923],"genre_scores_gemma":[0.7041181,0.03357122,0.2341716,0.01516588,0.004074967,0.003987119,0.003601118,0.0003348048,0.0009751226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3754917,"threshold_uncertainty_score":0.7701299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2453303529292534,"score_gpt":0.5476216045150109,"score_spread":0.3022912515857574,"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."}}