{"id":"W2907856445","doi":"","title":"Are transportation network companies revolutionizing urban mobility? A comparative media analysis on Uber in Paris and Montreal","year":2017,"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":"Institut National de la Recherche Scientifique","funders":"","keywords":"Transport engineering; Business; Regional science; Telecommunications; Engineering; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001386557,0.0003811932,0.0003083284,0.007065164,0.004526285,0.006682778,0.001138339,0.0007109122,0.01506405],"category_scores_gemma":[0.005093902,0.0003070954,0.0003235179,0.01482858,0.003009,0.003511874,0.001873271,0.00102721,0.0004447397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04585451,"about_ca_system_score_gemma":0.01590137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9666775,"about_ca_topic_score_gemma":0.981794,"domain_scores_codex":[0.9984404,0.0003973678,0.00002646681,0.0001476382,0.000296033,0.0006920747],"domain_scores_gemma":[0.99508,0.001826134,0.001081775,0.0001540875,0.001228097,0.0006299801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009228336,0.0003379603,0.5059459,0.0006927199,0.0004740545,0.002759509,0.1893755,0.00328234,0.001420189,0.1353123,0.05742801,0.1020486],"study_design_scores_gemma":[0.0000258636,0.00008312153,0.7734476,0.0003372133,0.0001604038,0.0001035267,0.1545351,0.0006675551,0.0004597405,0.0005556334,0.06954778,0.00007642179],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9050908,0.006180033,0.0002960038,0.005629196,0.00004838483,0.00005494125,0.004197718,0.00003756066,0.07846537],"genre_scores_gemma":[0.9881344,0.001991294,0.0001094941,0.0002388146,0.00002887605,0.00002316586,0.0006175426,0.00001967201,0.008836729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04585451,"threshold_uncertainty_score":0.3326993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03104925680039825,"score_gpt":0.2236268207695295,"score_spread":0.1925775639691313,"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."}}