{"id":"W4252852096","doi":"10.1093/geront/gnw162.303","title":"GERIATRIC TRAINING NEEDS OF RURAL EMERGENCY MEDICAL SERVICE PROVIDERS","year":2016,"lang":"en","type":"article","venue":"The Gerontologist","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; North York General Hospital; York University","funders":"","keywords":"Training (meteorology); Service (business); Medical emergency; Service provider; Medicine; Nursing; Business; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006457462,0.0001371197,0.0001564361,0.0002705393,0.0009069364,0.0005233939,0.0002034774,0.0005024833,0.01341337],"category_scores_gemma":[0.004807209,0.000104906,0.000152682,0.0002735197,0.0002138311,0.0003770183,0.0006424558,0.0005474039,0.0007543205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006006818,"about_ca_system_score_gemma":0.002304469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006634139,"about_ca_topic_score_gemma":0.02225737,"domain_scores_codex":[0.9996405,0.0001376092,0.00001658731,0.00002477811,0.00004755603,0.0001330191],"domain_scores_gemma":[0.9985126,0.0003047314,0.0002817515,0.00002833514,0.0003366895,0.0005359083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000343947,0.001565368,0.7615074,0.0008112888,0.00006076357,0.003528594,0.03807104,0.0006355951,0.006515742,0.0009532144,0.03280301,0.153204],"study_design_scores_gemma":[0.00006954306,0.0009641964,0.8693624,0.0003972659,0.00003730809,0.003233159,0.08187951,0.0009289021,0.0006229305,0.001238397,0.04122927,0.00003707383],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882445,0.0002329785,0.000200257,0.005215176,0.00006521314,0.00004095012,0.0001385551,0.000009603962,0.005852653],"genre_scores_gemma":[0.995068,0.0003764679,0.0005899139,0.001157676,0.00004507183,0.00004264129,0.000116578,0.000006124412,0.00259762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01341337,"threshold_uncertainty_score":0.04487216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09280574248810751,"score_gpt":0.424577458900225,"score_spread":0.3317717164121175,"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."}}