{"id":"W3124923335","doi":"","title":"I only get some satisfaction: Introducing satisfaction into measures of accessibility","year":2018,"lang":"en","type":"preprint","venue":"The Sydney eScholarship Repository (The University of Sydney)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Metropolitan area; TRIPS architecture; Index (typography); Public transport; Transport engineering; Measure (data warehouse); Business; Destinations; Quality (philosophy); Marketing; Geography; Computer science; Environmental economics; Engineering; Economics; Tourism; World Wide Web; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.004769694,0.0004282809,0.0007580574,0.0001958002,0.00297101,0.0001984779,0.00225001,0.0007180243,0.0002704339],"category_scores_gemma":[0.0006105885,0.0003507678,0.0005911884,0.0004689284,0.003625875,0.001290418,0.0006699548,0.001783135,0.00001965834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008777975,"about_ca_system_score_gemma":0.001813468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06598762,"about_ca_topic_score_gemma":0.0187265,"domain_scores_codex":[0.9941138,0.002157415,0.0008031495,0.0009928917,0.001467115,0.0004656309],"domain_scores_gemma":[0.9947987,0.000403873,0.001524166,0.002041397,0.0009907796,0.0002411351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004184831,0.0001435067,0.9569724,0.0005095339,0.0004405995,0.000009960633,0.02798773,0.00009811232,0.004023847,0.001240414,0.000579398,0.00757602],"study_design_scores_gemma":[0.0003257313,0.00005974473,0.9717198,0.0003818282,0.0005613252,0.000002170024,0.006016591,0.00001624245,0.003530167,0.01494349,0.002036112,0.0004067945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904298,0.0006630377,0.0003113066,0.001303613,0.002440346,0.0009308053,0.00003325935,0.0001496248,0.003738232],"genre_scores_gemma":[0.9975725,0.0002210131,0.0004188186,0.00005351764,0.0009747864,0.000002113568,0.00001479349,0.00002755263,0.0007149209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04726112,"threshold_uncertainty_score":0.9998944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02808625840917354,"score_gpt":0.2666540192283553,"score_spread":0.2385677608191818,"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."}}