{"id":"W2944586915","doi":"10.15353/cjo.78.480","title":"Get Your Training and Development Working for Your Bottom Line","year":2016,"lang":"en","type":"article","venue":"Canadian journal of optometry/CJO. Canadian journal of optometry","topic":"Human Resource Development and Performance Evaluation","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Line (geometry); Computer science; Geography; Mathematics; Geometry; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004431938,0.0005212644,0.0009992799,0.007425098,0.0007076851,0.0003479244,0.0009256117,0.0004284749,0.002613711],"category_scores_gemma":[0.0006133976,0.0004282669,0.0003098999,0.001315943,0.0002810065,0.0006159372,0.00002035935,0.0008963044,0.00005680493],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001273251,"about_ca_system_score_gemma":0.008146089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003020882,"about_ca_topic_score_gemma":0.001013577,"domain_scores_codex":[0.9951584,0.0001958639,0.002014957,0.0003711044,0.0007053194,0.001554362],"domain_scores_gemma":[0.9925843,0.0004059885,0.001678475,0.0002824264,0.001142594,0.003906142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001231745,0.00002206075,0.9008361,0.00004234815,0.0006646161,0.0004294809,0.01140131,0.00004473278,0.0000888764,0.00001784822,0.006704537,0.07962499],"study_design_scores_gemma":[0.004343511,0.0004670233,0.8486753,0.001021203,0.0001547795,0.002463086,0.005118958,0.00003323713,0.0002151422,0.00001368257,0.1367651,0.0007289591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844363,0.004206135,0.004706512,0.002086998,0.003150647,0.0003024326,0.00006817277,0.000008492441,0.001034263],"genre_scores_gemma":[0.9854812,0.00008163679,0.01054927,0.0004319222,0.001660439,0.00000802904,0.00001067369,0.0001035551,0.001673261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1300606,"threshold_uncertainty_score":0.9998169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1055185149306145,"score_gpt":0.3800218942258001,"score_spread":0.2745033792951856,"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."}}