{"id":"W4311874458","doi":"10.1177/03611981221140369","title":"Wheelchair Users’ Perspective on Transportation Service Hailed Through Uber and Lyft Apps","year":2022,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Wheelchair; Descriptive statistics; Service (business); Perspective (graphical); Applied psychology; Sample (material); Perception; Internet privacy; Psychology; Computer security; Transport engineering; Engineering; Advertising; Computer science; Business; Marketing; World Wide Web; Artificial intelligence","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":[0.001567616,0.0001977923,0.0002417253,0.0007953956,0.00275443,0.00413911,0.000357182,0.0009112409,0.005227354],"category_scores_gemma":[0.004984908,0.0001704622,0.0003139874,0.0008788158,0.001721552,0.004200829,0.002032309,0.0009018105,0.0006050357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009429487,"about_ca_system_score_gemma":0.0008897836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01398739,"about_ca_topic_score_gemma":0.0276722,"domain_scores_codex":[0.9978806,0.001275533,0.0001017412,0.00009503824,0.0003506454,0.0002965257],"domain_scores_gemma":[0.9973065,0.00132394,0.0004355145,0.00008034403,0.0004382184,0.0004155443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000109261,0.0001074414,0.1372919,0.0003194996,0.00004812199,0.003544799,0.7988261,0.0001704793,0.002384639,0.004730511,0.006342213,0.04612502],"study_design_scores_gemma":[0.000002158374,0.0001320581,0.05536086,0.000266127,0.00003355891,0.001665565,0.9102081,0.0002065249,0.0003974463,0.0003987145,0.03128295,0.00004590267],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982025,0.0008700233,0.0007148823,0.003915788,0.00004159837,0.00000885845,0.00009608327,0.00001885727,0.01230893],"genre_scores_gemma":[0.9960277,0.001073912,0.0002107119,0.0005948996,0.0000167464,0.000007528221,0.00003027243,0.000009506106,0.00202872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01398739,"threshold_uncertainty_score":0.02781194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07488246156418628,"score_gpt":0.3588039507342419,"score_spread":0.2839214891700556,"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."}}