{"id":"W1937270683","doi":"10.1002/atr.1180","title":"Fleet size determination for a truckload distribution center","year":2012,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Council","keywords":"Transport engineering; Center (category theory); Distribution (mathematics); Distribution center; Engineering; Mathematics; Business; Chemistry; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004934563,0.0004753185,0.0005594472,0.000906847,0.0006274896,0.0008849651,0.0008741544,0.0006594461,0.004520758],"category_scores_gemma":[0.00105348,0.0003111529,0.0005814933,0.0008029026,0.000283352,0.0006139544,0.0004194829,0.0005211306,0.0002593266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001945837,"about_ca_system_score_gemma":0.001109852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01422077,"about_ca_topic_score_gemma":0.01025461,"domain_scores_codex":[0.9996628,0.0000773122,0.000009648209,0.00007651008,0.00009738679,0.00007644575],"domain_scores_gemma":[0.999534,0.0002246957,0.00007584541,0.00003361539,0.00008550647,0.00004628005],"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":[0.00008036682,0.00003737048,0.0009336243,0.00004031659,0.000013014,0.000112898,0.00001831689,0.9793239,0.004359598,0.002182316,0.0006977022,0.01220072],"study_design_scores_gemma":[0.000008019856,0.00003231793,0.0009159213,0.000003400325,0.000006621347,0.00003568957,0.00003500238,0.9942575,0.002895161,0.001303068,0.0005004365,0.000006935169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5837736,0.0002320046,0.3992219,0.0004468642,0.00004055939,0.0001808678,0.0005414881,0.000519439,0.01504335],"genre_scores_gemma":[0.928283,0.00007431767,0.06644969,0.00002123441,0.000009125199,0.00005742321,0.000300583,0.00005641758,0.004748164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01422077,"threshold_uncertainty_score":0.02827603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008079725794617984,"score_gpt":0.2410657076957451,"score_spread":0.2329859819011271,"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."}}