{"id":"W3025930499","doi":"","title":"Macro-, Meso-, and Microlevel Validation of an Activity-Based Travel Demand Model","year":2014,"lang":"en","type":"article","venue":"Transportation Research Board 93rd Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transferability; Context (archaeology); Macro; Population; Travel behavior; Census; Geography; Computer science; Econometrics; Transport engineering; Demography; Economics; Engineering; Sociology","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":[0.01557971,0.0004261592,0.0007160097,0.001235508,0.001855659,0.0002551728,0.0008896132,0.0005346673,0.0001977635],"category_scores_gemma":[0.0005290327,0.0004522795,0.0002323567,0.001980276,0.002638425,0.001789497,0.00001086277,0.001402435,0.00001441702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001662589,"about_ca_system_score_gemma":0.001176182,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0216305,"about_ca_topic_score_gemma":0.04171278,"domain_scores_codex":[0.9882565,0.00282978,0.001208095,0.001355095,0.004701653,0.001648928],"domain_scores_gemma":[0.9926776,0.001435025,0.0003338526,0.0006793285,0.003910049,0.0009641271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005701451,0.00311267,0.6669855,0.002628342,0.0002318863,0.00007200937,0.1129746,0.01654402,0.1277215,0.04153844,0.0009213962,0.02156819],"study_design_scores_gemma":[0.003167045,0.0008589625,0.8903066,0.0002667519,0.00009915841,8.279382e-8,0.01115077,0.01172572,0.06866612,0.01103133,0.001901156,0.0008263249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790891,0.00007333122,0.01501755,0.001638378,0.00008664295,0.001629651,0.0004485793,0.0001682044,0.001848501],"genre_scores_gemma":[0.9932562,0.0001186477,0.005122212,0.00006369295,0.0001793526,0.0002197858,0.0003861006,0.00008387434,0.0005701635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2233211,"threshold_uncertainty_score":0.9997929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07453536409845525,"score_gpt":0.4086637862212839,"score_spread":0.3341284221228287,"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."}}