{"id":"W3207309403","doi":"10.1111/ajr.12817","title":"Return of the unexpected: Rural workforce recruitment and retention in the era of COVID‐19","year":2021,"lang":"en","type":"editorial","venue":"Australian Journal of Rural Health","topic":"Higher Education and Employability","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Workforce; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Business; Employee retention; Demographic economics; Economic growth; Medicine; Economics; Virology; Marketing; Outbreak; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00493359,0.0001528196,0.0005189292,0.00007490653,0.000275044,0.00005293784,0.0005564974,0.0003093501,0.0001353615],"category_scores_gemma":[0.001234639,0.00009361651,0.0002263802,0.0005863303,0.0004475426,0.0001275178,0.00002965787,0.001315262,4.403373e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006300011,"about_ca_system_score_gemma":0.004780064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01206904,"about_ca_topic_score_gemma":0.005037239,"domain_scores_codex":[0.994722,0.002511795,0.001122774,0.0001151989,0.001207651,0.0003205448],"domain_scores_gemma":[0.9967111,0.0006307308,0.001691821,0.0002797997,0.0004210035,0.0002655245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008521478,0.0001184872,0.01329903,0.0002553999,0.00002966467,0.000002610118,0.0591136,0.000005397326,0.00001207373,0.000375944,0.9238863,0.002816292],"study_design_scores_gemma":[0.0008755481,0.0004779497,0.03539613,0.002164863,0.00006795843,0.00001452143,0.1133589,1.571855e-7,0.00001329656,0.002409424,0.8450271,0.0001941058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4744437,0.002183837,0.000003635159,0.1230149,0.3990096,0.001101728,0.00008189189,0.000007462691,0.000153229],"genre_scores_gemma":[0.8177285,0.005182472,0.0001968019,0.0004202105,0.1724303,0.00001575094,0.00005014844,0.00002094734,0.003954914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3432848,"threshold_uncertainty_score":0.9945097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119580963222578,"score_gpt":0.4349386825432885,"score_spread":0.3229805862210307,"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."}}