{"id":"W1546645187","doi":"","title":"Winter Performance Measures in Alberta, Canada","year":2006,"lang":"en","type":"article","venue":"Transportation research circular","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Performance measurement; Work (physics); Winter storm; Asset (computer security); Public work; Performance indicator; Storm; Environmental resource management; Engineering; Computer science; Environmental science; Business; Geography; Meteorology; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004112579,0.00007553467,0.00008342776,0.00006112926,0.00008859336,0.0000189677,0.0001355914,0.00003938773,0.001080062],"category_scores_gemma":[0.00001232988,0.00007782847,0.00001966999,0.0003216128,0.0001214721,0.0001939263,0.000004715896,0.0001298573,0.0001437928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000367795,"about_ca_system_score_gemma":0.00008244162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9660017,"about_ca_topic_score_gemma":0.9939907,"domain_scores_codex":[0.9983895,0.00007248831,0.0002195509,0.000226493,0.0007701433,0.0003218031],"domain_scores_gemma":[0.9997197,0.00003236573,0.00002346109,0.0001530916,0.00002164188,0.00004975218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001409101,0.00001693383,0.9852379,0.00001204164,0.000002054953,0.00001797391,0.00007847755,0.003844423,0.009335995,0.00007339573,0.0009076396,0.0004590992],"study_design_scores_gemma":[0.0002050458,0.00001096784,0.9758477,0.00001012427,0.000001868966,0.000001508574,0.00003421294,0.0001390165,0.007421723,0.0001754797,0.01606676,0.0000856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971782,0.000008808654,0.00006679405,0.0002197377,0.0001007695,0.0001919971,0.000004917787,0.00001081513,0.002217955],"genre_scores_gemma":[0.9996248,0.000004648137,0.00005233552,0.00002530308,0.00002643141,0.00003474261,0.00003771844,0.0000106214,0.0001833944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02798899,"threshold_uncertainty_score":0.9998331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578746725165053,"score_gpt":0.2396991275524469,"score_spread":0.2239116603007964,"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."}}