{"id":"W3127468403","doi":"10.1139/cjce-2019-0465","title":"Material application methodologies for winter road maintenance: a renewed perspective","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Minnesota Department of Transportation; U.S. Department of Transportation","keywords":"Brine; Sustainability; Highway maintenance; Snow; Environmental science; Transport engineering; Computer science; Engineering; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002834428,0.00008433044,0.0001498677,0.00006633571,0.00004630872,0.00004716734,0.0001173374,0.00005034701,0.0005370456],"category_scores_gemma":[0.0003898106,0.00008414347,0.00007164245,0.0001020026,0.00004250993,0.0001628625,0.0000153636,0.00006267575,0.000007737923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005235397,"about_ca_system_score_gemma":0.0001117462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001684485,"about_ca_topic_score_gemma":0.06625369,"domain_scores_codex":[0.9993703,0.00002329979,0.0002046999,0.0001173778,0.00007656321,0.0002077842],"domain_scores_gemma":[0.9995502,0.00003021459,0.00009420584,0.0001048316,0.00006605095,0.0001544982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001207381,0.00001212084,0.01069709,0.00006423817,0.0001580251,0.0001633515,0.001741446,0.07252443,0.8947809,0.002669237,0.01195672,0.005111657],"study_design_scores_gemma":[0.003851071,0.0005399308,0.2915266,0.0004955054,0.0003383513,0.00664334,0.005757,0.01043071,0.4354723,0.02743159,0.2156936,0.001819926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7903823,0.0001415225,0.204293,0.0006826322,0.003117834,0.000187806,0.00003882587,0.00002382198,0.00113225],"genre_scores_gemma":[0.985003,0.000003875161,0.01463467,0.00003461124,0.0002568885,0.00001002706,0.000002680883,0.00001520731,0.00003905699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4593086,"threshold_uncertainty_score":0.9507847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300373196750486,"score_gpt":0.2282683677818078,"score_spread":0.2152646358143029,"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."}}