{"id":"W7095781335","doi":"","title":"Canadian Labour Market and Skills Researcher Network Working Paper Number: 29, DRAFT","year":2015,"lang":"en","type":"article","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human resources; Government (linguistics); Human capital; Work (physics); Human resource management","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008183276,0.0006342008,0.001128557,0.004729163,0.005015874,0.005950412,0.001963087,0.001827998,0.1569246],"category_scores_gemma":[0.03701857,0.0005210002,0.0005144699,0.009455608,0.001152987,0.002207183,0.001687094,0.001980679,0.02890067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05905301,"about_ca_system_score_gemma":0.2087895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9537393,"about_ca_topic_score_gemma":0.9608623,"domain_scores_codex":[0.9948233,0.0005159015,0.0002790814,0.0004721907,0.003044613,0.0008649486],"domain_scores_gemma":[0.966998,0.003444788,0.000565521,0.00118557,0.02526806,0.002537983],"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":[0.00003883657,0.00002041185,0.001458857,0.0001286779,0.000008180667,0.00001484337,0.000259859,0.000142234,0.00003083641,0.008586026,0.9760367,0.01327467],"study_design_scores_gemma":[0.00007254229,0.00001966432,0.01975031,0.0007336268,0.00003921507,0.00001685777,0.00151517,0.0005325115,0.0002374853,0.003128131,0.9739168,0.00003769055],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008183353,0.005579998,0.001700007,0.0739448,0.005092426,0.001576219,0.3075694,0.0004897714,0.595864],"genre_scores_gemma":[0.1012197,0.009830229,0.006278188,0.006500124,0.0007363278,0.001910954,0.1559492,0.0006961863,0.7168791],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8430755,"threshold_uncertainty_score":0.5249649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02687519469214022,"score_gpt":0.3074672935888455,"score_spread":0.2805920988967053,"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."}}