{"id":"W2909893247","doi":"10.1111/cag.12514","title":"Ride‐hailing's impact on Canadian cities: Now let's consider the long game","year":2019,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Taxis; Key (lock); Business; Marketing; Advertising; Transport engineering; Engineering; Computer science; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001671945,0.0007839742,0.0006049947,0.001644676,0.01150243,0.007305578,0.001889803,0.002150419,0.02314918],"category_scores_gemma":[0.00692536,0.0002024178,0.000830295,0.003368167,0.004019384,0.002893982,0.002751499,0.003220195,0.0008938011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1253144,"about_ca_system_score_gemma":0.1845272,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9976302,"about_ca_topic_score_gemma":0.9989801,"domain_scores_codex":[0.9970987,0.0001982188,0.00004254392,0.0001423609,0.001241464,0.001276789],"domain_scores_gemma":[0.9947473,0.0003284709,0.0001784165,0.0000919645,0.003562361,0.001091346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003405069,0.0001639948,0.05273416,0.001110168,0.0001617718,0.0005871381,0.006140686,0.005130444,0.001125439,0.1399959,0.6352311,0.1572788],"study_design_scores_gemma":[0.00006481985,0.0001602467,0.1580777,0.001047481,0.0002122092,0.0001421967,0.02863324,0.002097018,0.0009292354,0.01238027,0.7958576,0.0003980319],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1571632,0.02353933,0.001520803,0.4941355,0.003250313,0.0001817555,0.01000754,0.0002884544,0.3099131],"genre_scores_gemma":[0.8839548,0.01994119,0.001732211,0.02235959,0.0004693915,0.00006305811,0.00181069,0.0001037211,0.06956536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1253144,"threshold_uncertainty_score":0.9092237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006846992074883867,"score_gpt":0.1961657082652282,"score_spread":0.1893187161903443,"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."}}