{"id":"W7133276684","doi":"","title":"Phase 1: Evaluation of leading and lagging performance indicators","year":2021,"lang":"en","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lagging; Dangerous goods; Performance indicator; Root cause; Control (management); Economic indicator; Risk assessment","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":[0.03563299,0.001985563,0.001560437,0.006446896,0.001388841,0.003333691,0.001917352,0.0008599426,0.006281223],"category_scores_gemma":[0.06238287,0.0006964695,0.003504084,0.006309107,0.0009609176,0.00276653,0.002988296,0.001588454,0.002400745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006567067,"about_ca_system_score_gemma":0.02785929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04370065,"about_ca_topic_score_gemma":0.04149006,"domain_scores_codex":[0.981203,0.004411886,0.00174774,0.001571992,0.00919092,0.001874364],"domain_scores_gemma":[0.8880179,0.02400746,0.01351265,0.004807868,0.06615344,0.003500763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003768993,0.004277842,0.7494034,0.002809775,0.0007376874,0.000170275,0.00293713,0.01437409,0.002418595,0.005857391,0.01584774,0.1973971],"study_design_scores_gemma":[0.0005819375,0.009656567,0.9110287,0.000899622,0.0007263768,0.0001102697,0.007594414,0.0231146,0.01037125,0.002313085,0.03337298,0.0002302631],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8068976,0.0007147485,0.03960805,0.0007616807,0.0002000579,0.06309105,0.06168645,0.001058965,0.02598144],"genre_scores_gemma":[0.764154,0.000615843,0.08999353,0.0002573197,0.00009810283,0.08018279,0.05441112,0.000267284,0.01002009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04370065,"threshold_uncertainty_score":0.1884475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174861641675103,"score_gpt":0.2816239918168161,"score_spread":0.2641378276493058,"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."}}