{"id":"W1999464453","doi":"10.1186/1472-6963-10-50","title":"The \"Medicine in Australia: Balancing Employment and Life (MABEL)\" longitudinal survey - Protocol and baseline data for a prospective cohort study of Australian doctors' workforce participation","year":2010,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"Nursing research; Medicine; Health administration; Workforce; Baseline (sea); Health informatics; Public health; Cohort; Cohort study; Health services research; Quality of Life Research; Health economics; Protocol (science); Family medicine; Gerontology; Nursing; Alternative medicine; Economic growth; Internal medicine","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.03512491,0.0002609922,0.0007113764,0.0002235626,0.001688424,0.0000419301,0.0006514779,0.0002187406,0.00006452961],"category_scores_gemma":[0.001604793,0.0001798605,0.00001332951,0.0009845922,0.0002872022,0.0002568117,0.0006393112,0.001472141,0.000006040039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002529274,"about_ca_system_score_gemma":0.0009916143,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09371106,"about_ca_topic_score_gemma":0.5569684,"domain_scores_codex":[0.9904518,0.004068424,0.001826965,0.000935429,0.001083558,0.001633837],"domain_scores_gemma":[0.9907851,0.00566294,0.0005553238,0.001262508,0.0009866421,0.0007474783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001453089,0.0003116188,0.9863063,0.003512659,0.00001843941,9.760339e-7,0.007136323,0.000009618931,0.000005797448,0.0001305545,0.0007245584,0.0003900448],"study_design_scores_gemma":[0.003843111,0.001558835,0.9739925,0.001310946,0.00001078472,6.083421e-7,0.01173401,0.002220124,0.000001872581,0.00007832485,0.005125945,0.0001229284],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8525172,0.00006073514,0.00001147909,0.001397824,0.0001574892,0.1456912,0.000107322,0.00002753128,0.0000292074],"genre_scores_gemma":[0.9178618,0.00004632922,0.0002469099,0.0001401454,0.0003032508,0.08063324,0.0001337667,0.00003195145,0.0006026172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4632573,"threshold_uncertainty_score":0.9996113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2900017130144297,"score_gpt":0.5998543810508277,"score_spread":0.309852668036398,"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."}}