{"id":"W3123424290","doi":"10.32920/ryerson.14637975.v1","title":"The Impact of Aggregate and Sectoral Fluctuations on Training Decisions","year":2021,"lang":"en","type":"article","venue":"","topic":"Economic Policies and Impacts","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Acadia University","funders":"","keywords":"Aggregate (composite); Training (meteorology); Economics; Business; Econometrics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003574382,0.000340891,0.0009099468,0.0007813501,0.0007025118,0.004145141,0.0005353711,0.002441555,0.00688971],"category_scores_gemma":[0.01462705,0.0003886462,0.0005452935,0.001917558,0.001074326,0.001689682,0.001350293,0.002397121,0.0008148348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003325309,"about_ca_system_score_gemma":0.001701645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03136334,"about_ca_topic_score_gemma":0.0313849,"domain_scores_codex":[0.997508,0.0006871006,0.0001628419,0.0002856029,0.0002893382,0.001067115],"domain_scores_gemma":[0.9845272,0.007027983,0.004320701,0.0004033278,0.001394954,0.002325831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002662711,0.00106948,0.5717652,0.0002074412,0.0006057192,0.001070157,0.0006973355,0.3053128,0.003993717,0.05724426,0.01315748,0.04221372],"study_design_scores_gemma":[0.00009364125,0.0004000288,0.8297929,0.00007226366,0.0001903073,0.0001471406,0.002631121,0.1241372,0.001572027,0.03478792,0.006079735,0.00009561336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9730912,0.0008063246,0.002324902,0.008385278,0.000125169,0.00002851363,0.002080054,0.00006874606,0.0130898],"genre_scores_gemma":[0.9977037,0.0001897709,0.00007290297,0.0001961569,0.00003980394,0.000004585695,0.0002428084,0.00000718524,0.001543104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03136334,"threshold_uncertainty_score":0.06236154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09876666996273861,"score_gpt":0.291162169509008,"score_spread":0.1923954995462694,"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."}}