{"id":"W2099449314","doi":"10.1109/hicss.2014.130","title":"Decision Support for Capacitated Arc Routing for Providing Municipal Waste and Recycling Services","year":2014,"lang":"en","type":"article","venue":"","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Arc routing; Truck; Decision support system; Routing (electronic design automation); Transparency (behavior); Vehicle routing problem; Waste collection; Computer science; Operations research; Transport engineering; Engineering; Waste management; Waste treatment; Computer network; Computer security","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.001212373,0.0001591356,0.0001827321,0.0000395037,0.0002985342,0.00008846218,0.0002782546,0.00005439713,0.0001885394],"category_scores_gemma":[0.0001177075,0.0001367892,0.00005499137,0.00009776519,0.00005229766,0.0002394444,0.000409687,0.00005733466,0.0000294958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007020586,"about_ca_system_score_gemma":0.000002075597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005414922,"about_ca_topic_score_gemma":0.001158896,"domain_scores_codex":[0.9986058,0.00003195524,0.0003172569,0.0004143204,0.0001988192,0.0004318002],"domain_scores_gemma":[0.9990853,0.0003919108,0.0001135441,0.0002865905,0.00001053146,0.0001121175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001433496,0.0004710492,0.03597577,0.001816063,0.0002554037,0.000005429269,0.02657306,0.2891199,0.02907973,0.01587706,0.00635989,0.5930332],"study_design_scores_gemma":[0.0009305294,0.0002170054,0.0002950749,0.00005813882,0.00003237402,0.000001437621,0.002216004,0.9660263,0.001544649,0.002026777,0.02641836,0.0002333455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8983448,0.000006013861,0.07970476,0.0001738896,0.0001662817,0.001293528,0.000005832509,0.00006622185,0.02023872],"genre_scores_gemma":[0.9426824,0.000004179503,0.05462408,0.0003360998,0.00005460265,0.0001064772,0.00001326817,0.00002678207,0.002152054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6769064,"threshold_uncertainty_score":0.5578103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078274375638238,"score_gpt":0.2653425164175521,"score_spread":0.2445597726611697,"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."}}