{"id":"W2543066411","doi":"","title":"Maximizing Opportunity, Minimizing Risk: Aligning Law, Policy and Practice to Strengthen Work-Integrated Learning in Ontario","year":2016,"lang":"en","type":"article","venue":"","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Economics; Business; Risk analysis (engineering); Law; Actuarial science; Political science; Engineering","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":[0.008137657,0.000257043,0.0004097473,0.00169494,0.02640302,0.0112695,0.003381459,0.002229458,0.006866311],"category_scores_gemma":[0.01378272,0.0006153666,0.0004677882,0.003395749,0.01266096,0.00395327,0.0120873,0.002674579,0.0004856933],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.251885,"about_ca_system_score_gemma":0.5019919,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9836939,"about_ca_topic_score_gemma":0.9954512,"domain_scores_codex":[0.988691,0.002339546,0.0003609358,0.0007479264,0.003346623,0.004514016],"domain_scores_gemma":[0.97857,0.003082242,0.00160554,0.0009351476,0.004935009,0.01087213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002427936,0.0004218378,0.1466334,0.001290075,0.0000882302,0.003577695,0.2887385,0.003514902,0.003942341,0.2391322,0.06608044,0.2463376],"study_design_scores_gemma":[0.00004896462,0.0001589207,0.1323865,0.0008686747,0.00005288302,0.0002748806,0.2398816,0.002315985,0.001213734,0.02784243,0.5948136,0.0001418125],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5718216,0.004765009,0.01082597,0.1471257,0.0004291756,0.000956603,0.0004791372,0.000216728,0.2633801],"genre_scores_gemma":[0.9363447,0.002155371,0.006324583,0.003922602,0.00005088807,0.0001964751,0.0001295377,0.00006904237,0.05080675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.251885,"threshold_uncertainty_score":0.8677073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.118805739084843,"score_gpt":0.3950207078756086,"score_spread":0.2762149687907655,"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."}}