{"id":"W2119213263","doi":"","title":"How is own account transport well adapted to urban environments?","year":2010,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000671646,0.000242071,0.0002087288,0.0001064553,0.0001421423,0.0001366001,0.0006104234,0.0001606737,0.000502316],"category_scores_gemma":[0.00006129865,0.0002548632,0.0001064055,0.0002610828,0.0001214388,0.0001624644,0.00003705945,0.0003955621,0.0001678785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004337297,"about_ca_system_score_gemma":0.000024695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001003139,"about_ca_topic_score_gemma":0.0008814025,"domain_scores_codex":[0.998603,0.0001382167,0.0002621193,0.0003522972,0.0002961026,0.0003482185],"domain_scores_gemma":[0.998248,0.0001424398,0.00005343464,0.00113735,0.0001613489,0.0002574378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005942578,0.00220685,0.05705969,0.0003338204,0.0004873323,0.00008779958,0.0425862,0.0007594079,0.5811217,0.205781,0.05301259,0.05650413],"study_design_scores_gemma":[0.0004517136,4.574154e-7,0.01295726,0.00007934234,0.0000383683,0.000004631269,0.00005887619,0.007013942,0.1341067,0.000172656,0.844699,0.0004170423],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.323259,0.0004943281,0.5213303,0.008387157,0.0007194892,0.0006406499,0.0002190214,0.0008209436,0.1441291],"genre_scores_gemma":[0.9683133,0.0001104449,0.01585559,0.0001619654,0.00003280822,0.00002473928,0.000157974,0.00005615052,0.01528703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7916864,"threshold_uncertainty_score":0.9999903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009907228856095357,"score_gpt":0.1703140027545554,"score_spread":0.1604067738984601,"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."}}