{"id":"W3121751124","doi":"","title":"Probabilistic Modeling of Freight Consolidation by Private Carriage","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; University of Waterloo","funders":"","keywords":"Carriage; Consolidation (business); Probabilistic logic; Business; Computer science; Transport engineering; Engineering; Finance; Artificial intelligence; Structural engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001558797,0.000825169,0.001348169,0.00125134,0.000634188,0.002378199,0.002213714,0.001829932,0.005342468],"category_scores_gemma":[0.003536037,0.001397987,0.00132654,0.002120717,0.001460509,0.002604486,0.00120515,0.001567751,0.0007558503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001980505,"about_ca_system_score_gemma":0.001237739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03227767,"about_ca_topic_score_gemma":0.02085898,"domain_scores_codex":[0.9990758,0.0003169776,0.00003395486,0.0002038997,0.0001376868,0.0002316558],"domain_scores_gemma":[0.9980944,0.001013285,0.0003449158,0.0001295407,0.0002632388,0.0001546614],"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":[0.00002716212,0.00001862406,0.000698039,0.000006032742,0.00001225007,0.00002741951,0.00001813208,0.9856499,0.000131145,0.01156048,0.0002723909,0.001578451],"study_design_scores_gemma":[0.000002864825,0.00000634496,0.000193355,0.00000139937,0.000004744475,0.000005686446,0.000006607083,0.9970328,0.00003375876,0.002602216,0.0001068957,0.000003358272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.393819,0.0006879188,0.5918562,0.001070683,0.00009811741,0.0001255185,0.001103112,0.0004345184,0.0108049],"genre_scores_gemma":[0.9749019,0.0003876144,0.00786695,0.00003918255,0.0000469625,0.00009413552,0.0004405705,0.00005380239,0.01616883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03227767,"threshold_uncertainty_score":0.0641796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134301001920977,"score_gpt":0.2000539248240566,"score_spread":0.1787109148048468,"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."}}