{"id":"W4213448920","doi":"10.1177/03611981221077264","title":"Optimization Models for Snowplow Routes and Depot Locations: A Real-World Implementation","year":2022,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"CIMA+ (Canada); University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Truck; Transport engineering; Task (project management); Computer science; Operations research; Service (business); Benchmarking; Routing (electronic design automation); Yard; Vehicle routing problem; Engineering; Business; Systems engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004202622,0.0001853523,0.0002812066,0.0006702551,0.001587245,0.0001340125,0.000614771,0.00006299955,0.001283048],"category_scores_gemma":[0.0000550513,0.0001641224,0.0001823911,0.001691658,0.0004704785,0.001064173,0.00002628698,0.0007598904,0.00000521138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006330811,"about_ca_system_score_gemma":0.0002412452,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02730747,"about_ca_topic_score_gemma":0.106555,"domain_scores_codex":[0.9942979,0.000992337,0.001117139,0.000416159,0.002579683,0.0005967907],"domain_scores_gemma":[0.9977775,0.0005719831,0.0004935596,0.0003146254,0.0006301995,0.0002121807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001404599,0.0002051575,0.5528376,0.0001185625,0.00009742458,0.00001235995,0.00311446,0.4189597,0.004151695,0.004952986,0.006869218,0.007276232],"study_design_scores_gemma":[0.002835534,0.0009441631,0.9414514,0.00006726792,0.0001061483,0.00000257632,0.006358791,0.01741525,0.001849578,0.01898598,0.009660241,0.0003230201],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767823,0.00004890647,0.01821014,0.002338439,0.0004945517,0.001836345,0.000152404,0.00002813283,0.0001087966],"genre_scores_gemma":[0.985615,0.0004200992,0.01284924,0.00004788462,0.0001008036,0.0005777616,0.00008683283,0.00005162399,0.0002508184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4015445,"threshold_uncertainty_score":0.9997125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0724319808981939,"score_gpt":0.369904233317367,"score_spread":0.2974722524191731,"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."}}