{"id":"W2802712405","doi":"","title":"Freight flows and urban systems: some evidence from France","year":2013,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Computer science; Environmental science","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":[0.002370961,0.0003958772,0.0004515951,0.005209,0.001420983,0.003037262,0.0006876034,0.00083833,0.006133692],"category_scores_gemma":[0.006899544,0.0002362389,0.0004918309,0.009207426,0.00179393,0.001452809,0.001338683,0.0006128557,0.0003473137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003876904,"about_ca_system_score_gemma":0.001341757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2851813,"about_ca_topic_score_gemma":0.2567424,"domain_scores_codex":[0.9980137,0.0009700567,0.00007738493,0.0002664348,0.0003009943,0.0003714478],"domain_scores_gemma":[0.9877253,0.007702417,0.002274007,0.0004578153,0.001495476,0.0003449611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003974595,0.000216996,0.9187069,0.0003286528,0.0006888296,0.0006209532,0.009554724,0.003395402,0.0003851593,0.01921778,0.004981006,0.04150607],"study_design_scores_gemma":[0.00002032423,0.00009502942,0.9812561,0.0001608559,0.0001229316,0.0001082375,0.00611777,0.0005118132,0.0001424769,0.001232798,0.01020538,0.00002632048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974462,0.005512232,0.0005403662,0.002152486,0.00001735797,0.00001364099,0.001505025,0.00001439062,0.01578247],"genre_scores_gemma":[0.9963444,0.001661302,0.000179343,0.0001635294,0.000035529,0.00000877901,0.0006732482,0.000005697453,0.0009282323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2851813,"threshold_uncertainty_score":0.5670426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01907344319630544,"score_gpt":0.1886890372576313,"score_spread":0.1696155940613258,"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."}}