{"id":"W6969272221","doi":"10.5683/sp3/marslq","title":"Determining Preference for Transit-Integrated Ridesourcing Models in Northwest Waterloo, Ontario, 2022 [Waterloo, Ontario, Canada]","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preference; TRIPS architecture; Revealed preference; Statistical analysis","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":[0.0009325209,0.0007022684,0.0006122998,0.001181698,0.001199914,0.00136275,0.001615591,0.0006262178,0.008660579],"category_scores_gemma":[0.005386629,0.000313125,0.0006691951,0.003842613,0.0004368605,0.000538704,0.0007043016,0.0005759037,0.003538145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0109306,"about_ca_system_score_gemma":0.01152343,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9795536,"about_ca_topic_score_gemma":0.9924665,"domain_scores_codex":[0.9991614,0.0001518769,0.00005936161,0.0002043939,0.0002565462,0.0001665377],"domain_scores_gemma":[0.9979551,0.0003793565,0.0001598129,0.0002092642,0.001057302,0.0002392246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005988498,0.0001908663,0.1540047,0.001210455,0.000257023,0.0002016196,0.001035719,0.005687231,0.0007017152,0.001917577,0.8069145,0.02727969],"study_design_scores_gemma":[0.0004543819,0.0001106562,0.5790802,0.000960071,0.0002355633,0.0001650555,0.006254903,0.02267452,0.0009887638,0.001221113,0.3876813,0.0001735764],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1169484,0.001003064,0.001151198,0.0008304696,0.00008270197,0.0002295256,0.8662632,0.0004504843,0.01304103],"genre_scores_gemma":[0.1294432,0.0004903064,0.002976649,0.0001858061,0.00001707799,0.0002654817,0.8578929,0.0001297763,0.008598853],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02044642,"threshold_uncertainty_score":0.07930744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03404256274715851,"score_gpt":0.2259983427700044,"score_spread":0.1919557800228459,"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."}}