{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001229713,0.0006759514,0.0003707252,0.0005606306,0.00052814,0.00161338,0.00157184,0.0007172416,0.006372822],"category_scores_gemma":[0.004210083,0.0003452863,0.0003851334,0.0004982328,0.000327943,0.0008705042,0.0005838166,0.0005864134,0.0008466056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009736013,"about_ca_system_score_gemma":0.001409092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005325886,"about_ca_topic_score_gemma":0.005870849,"domain_scores_codex":[0.9991036,0.0002716469,0.00006986663,0.0001809301,0.0002884111,0.00008541775],"domain_scores_gemma":[0.997716,0.001201715,0.0001698247,0.0002101768,0.0005903963,0.0001119046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008568022,0.0006278245,0.003627642,0.0005692054,0.0000817258,0.0005874496,0.0004814062,0.5574365,0.04222978,0.01025881,0.005763359,0.3774796],"study_design_scores_gemma":[0.0001028726,0.0002287355,0.0006162692,0.00003781149,0.00003829995,0.0001042748,0.0001401591,0.9661537,0.02072342,0.002169014,0.009650453,0.00003496994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1599386,0.0001880033,0.8127506,0.0006299149,0.00009544256,0.001089032,0.0007036127,0.008793675,0.01581114],"genre_scores_gemma":[0.6857767,0.0001314597,0.3092147,0.00009518395,0.00001569926,0.000311194,0.0005446455,0.0001300586,0.003780318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006372822,"threshold_uncertainty_score":0.02131915,"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."}}