{"id":"W574081526","doi":"","title":"Los Angeles Cargo Forecasting Model Development","year":2007,"lang":"en","type":"article","venue":"11th World Conference on Transport ResearchWorld Conference on Transport Research Society","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Metropolitan area; Transport engineering; Calibration; Commodity; Operations research; Computer science; Geography; Engineering; Business; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004091917,0.0007888686,0.0004851015,0.0007507696,0.0005116313,0.001181175,0.001631722,0.0005579202,0.01355547],"category_scores_gemma":[0.00121258,0.0004501252,0.0006338989,0.001154017,0.0001558683,0.001078772,0.0005694276,0.0009688405,0.004274493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001982573,"about_ca_system_score_gemma":0.002513572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1623556,"about_ca_topic_score_gemma":0.07304832,"domain_scores_codex":[0.9997966,0.00003998238,0.00001192559,0.00004993347,0.00007583322,0.00002576142],"domain_scores_gemma":[0.9995531,0.00005660107,0.00002388531,0.00002934986,0.0003190548,0.00001799153],"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":[0.0000390871,0.00004067176,0.002396535,0.00004766905,0.00002598959,0.0000797312,0.00004388603,0.9068128,0.0002698746,0.009740582,0.05216565,0.02833749],"study_design_scores_gemma":[0.00001404974,0.000007031798,0.0004606751,0.00001545704,0.000008365101,0.00001216537,0.00001903194,0.9723741,0.0003245815,0.001474082,0.02527839,0.00001216817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1146109,0.001267308,0.4510454,0.004196622,0.0007971265,0.0008275941,0.06583361,0.01971526,0.3417062],"genre_scores_gemma":[0.547905,0.00215034,0.2233793,0.0003997473,0.0002120446,0.001867185,0.07864019,0.001799694,0.1436466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1623556,"threshold_uncertainty_score":0.3228211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2926587272113089,"score_gpt":0.3354846302596264,"score_spread":0.04282590304831746,"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."}}