{"id":"W2789052329","doi":"","title":"Minimising skills wastage: Maximising the health of skilled migrant groups","year":2017,"lang":"en","type":"article","venue":"eCite Digital Repository (University of Tasmania)","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Government (linguistics); Immigration; Qualitative property; Data collection; Public relations; Qualitative research; Exploratory research; Census; Human capital; Business; Political science; Economic growth; Sociology; Medicine; Population; Economics; Environmental health","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":[],"consensus_categories":[],"category_scores_codex":[0.004662962,0.0003433918,0.0002868371,0.0008097501,0.002025965,0.001953671,0.001183807,0.0009708419,0.007221898],"category_scores_gemma":[0.008199899,0.0001800323,0.0003677112,0.0004415626,0.001166844,0.001533579,0.005985108,0.0007456871,0.0009028164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478974,"about_ca_system_score_gemma":0.009488469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008872466,"about_ca_topic_score_gemma":0.01493452,"domain_scores_codex":[0.9974534,0.001494284,0.0000523403,0.0001004508,0.0003192989,0.0005802962],"domain_scores_gemma":[0.9977899,0.0004456174,0.0003540533,0.0001198268,0.000320115,0.0009705566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003122072,0.001645632,0.06380703,0.002432835,0.00007692347,0.0007814352,0.03816135,0.001115814,0.005634968,0.006059031,0.01816643,0.8618062],"study_design_scores_gemma":[0.000364236,0.01179665,0.5407138,0.008827574,0.0003298717,0.001554907,0.1631596,0.006033208,0.01010986,0.02699881,0.2299469,0.0001646471],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9063697,0.002707119,0.008453564,0.0322748,0.0003469625,0.0007879626,0.0001906219,0.0001780576,0.04869137],"genre_scores_gemma":[0.9760829,0.00195278,0.0111087,0.001994794,0.00007996926,0.0004115619,0.0000789113,0.00002098775,0.008269506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008872466,"threshold_uncertainty_score":0.02466041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02774365919765756,"score_gpt":0.3074112098140289,"score_spread":0.2796675506163713,"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."}}