{"id":"W4392545100","doi":"10.1371/journal.pone.0294651","title":"Effectiveness of rural internships for veterinary students to combat veterinary workforce shortages in rural areas","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Internship; Workforce; Veterinary medicine; Rural area; Medicine; Work (physics); Economic shortage; Livestock; Animal welfare; Animal health; Public health; Medical education; Government (linguistics); Nursing; Economic growth; Geography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001376998,0.0002941824,0.0007444319,0.0002722174,0.0001751689,0.00002455422,0.0005202149,0.0002339519,0.0001021522],"category_scores_gemma":[0.0002202616,0.0002811591,0.0001038071,0.000467818,0.00005567038,0.0001813333,0.0004861636,0.0005741867,0.0001668084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005250742,"about_ca_system_score_gemma":0.0001032973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003275237,"about_ca_topic_score_gemma":0.0000551482,"domain_scores_codex":[0.996616,0.0008774084,0.0008030264,0.0003272575,0.0005242646,0.0008520221],"domain_scores_gemma":[0.9969148,0.002171632,0.0001033047,0.0004126505,0.0001489006,0.0002487362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008497794,0.002452802,0.8916202,0.04129628,0.0004774028,0.0001522116,0.01114904,0.00003437925,0.0364102,0.001445521,0.001123295,0.005340901],"study_design_scores_gemma":[0.004160311,0.01016553,0.7218643,0.2342609,0.0002750519,0.00001253652,0.0194725,0.0008195295,0.003427852,0.001819096,0.002624227,0.001098148],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921914,0.001731583,0.00006091991,0.0002869669,0.0007556704,0.004170944,0.0001076799,0.0002037146,0.0004910977],"genre_scores_gemma":[0.9961714,0.0001197393,0.0004497424,0.0001599256,0.0001790337,0.001706705,0.0000767518,0.00007583848,0.001060923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1929646,"threshold_uncertainty_score":0.9999641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1578353217236977,"score_gpt":0.4661970488045424,"score_spread":0.3083617270808447,"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."}}