{"id":"W610994705","doi":"","title":"Travel behavior of low income older adults and development of an Accessibility calculator","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spouse; Neighbourhood (mathematics); Socioeconomic status; Car ownership; Multilevel model; Demography; Population; Travel behavior; Geography; Credence; Household income; Multinomial logistic regression; Psychology; Gerontology; Medicine; Public transport; Transport engineering; Sociology; Mathematics; Statistics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.01379727,0.0003700313,0.0007758376,0.001026068,0.000932854,0.0001082624,0.001005081,0.0004674655,0.0002641869],"category_scores_gemma":[0.0005563109,0.0003715036,0.0001598916,0.002168884,0.002834467,0.001696176,0.0000201229,0.00108499,0.00001025643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00024482,"about_ca_system_score_gemma":0.00314255,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03944245,"about_ca_topic_score_gemma":0.1082481,"domain_scores_codex":[0.9878789,0.00157257,0.002039482,0.001197909,0.005888927,0.001422177],"domain_scores_gemma":[0.989468,0.0006131702,0.0004181372,0.0006527866,0.007330828,0.001517124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001648945,0.001307222,0.8358063,0.00102462,0.00004937734,0.00004271424,0.1478964,0.00002409033,0.0009217461,0.0009035415,0.00005083459,0.0103243],"study_design_scores_gemma":[0.002135874,0.0003399801,0.9197708,0.0003566635,0.00002897982,5.542928e-8,0.06774679,0.00003187846,0.008665302,0.0003454067,0.0002431495,0.0003351144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956322,0.0002203549,0.0002951314,0.0001749092,0.0001286881,0.002508458,0.0003985344,0.00009792457,0.0005437754],"genre_scores_gemma":[0.9943194,0.00005062012,0.004578207,0.00001062669,0.0001049083,0.0003561818,0.0003540881,0.00005558719,0.0001704048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08396456,"threshold_uncertainty_score":0.9998792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08053872285860525,"score_gpt":0.4222358140437282,"score_spread":0.341697091185123,"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."}}