{"id":"W1970112009","doi":"10.3141/2230-01","title":"Investigating the Role of Social Networks in Start Time and Duration of Activities","year":2011,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Endogeneity; Duration (music); Relevance (law); Travel behavior; Context (archaeology); Econometrics; Scheduling (production processes); Econometric model; Time allocation; Computer science; Psychology; Economics; Microeconomics; Operations management; Geography; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006211434,0.0001267568,0.0003198783,0.0005696432,0.0006695437,0.00004261071,0.0005122003,0.0001688436,0.0001625707],"category_scores_gemma":[0.0002110834,0.00009429044,0.0001461058,0.001655143,0.001565455,0.000633148,0.000003469699,0.00100085,8.808763e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007484678,"about_ca_system_score_gemma":0.0005464126,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02349536,"about_ca_topic_score_gemma":0.07711475,"domain_scores_codex":[0.9945551,0.001624655,0.001204404,0.0001892746,0.001985403,0.0004412154],"domain_scores_gemma":[0.9965313,0.0009363142,0.0006997638,0.0001543873,0.001550777,0.0001274293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007591409,0.0002070884,0.7797532,0.0001033556,0.00008976115,0.000007287136,0.1819906,0.003693218,0.003401708,0.02381909,0.0002998799,0.005875656],"study_design_scores_gemma":[0.0005872481,0.0001948963,0.9614577,0.0002022967,0.00003085472,8.28874e-8,0.03008953,0.0006708748,0.001558035,0.004232931,0.0008796912,0.00009588674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969866,0.0001742871,0.0003744245,0.0009603265,0.0001013666,0.0005474457,0.00003061779,0.00001062521,0.0008143158],"genre_scores_gemma":[0.9981749,0.0004462524,0.001081004,0.0000134894,0.0000686189,0.00001976583,0.00001307109,0.00001895119,0.0001639367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1817045,"threshold_uncertainty_score":0.9830073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0801667180968357,"score_gpt":0.3565217242938685,"score_spread":0.2763550061970328,"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."}}