{"id":"W3216584402","doi":"10.1155/2021/5398316","title":"Modeling and Quantifying Interaction of Information and Capacity in Public Transport Disruptions","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Microsimulation; Computer science; Public transport; Perspective (graphical); Service (business); Transport engineering; Transportation planning; Operations research; Engineering; Business; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003950238,0.00005946012,0.0001521932,0.0002223101,0.00009825468,0.00002339427,0.00003002449,0.00005963115,0.000007854364],"category_scores_gemma":[0.00007732163,0.00006452211,0.00003671513,0.0003073161,0.00004713224,0.002506458,3.99879e-7,0.0001371614,8.58654e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003015986,"about_ca_system_score_gemma":0.0001217838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001819409,"about_ca_topic_score_gemma":0.005085276,"domain_scores_codex":[0.9989687,0.00004706944,0.0006006706,0.00006750421,0.0002240483,0.00009201923],"domain_scores_gemma":[0.9991597,0.00004920982,0.0002836128,0.00003298414,0.0004126537,0.00006183333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001331377,0.00008336961,0.1512179,0.0001405353,0.00002481434,0.000009938687,0.090693,0.728029,0.001620537,0.01471052,7.165803e-7,0.01333657],"study_design_scores_gemma":[0.001924431,0.00008243047,0.9177246,0.0004479044,0.00008590103,0.00001336494,0.06771678,0.008875622,0.0004252196,0.001713756,0.0007846738,0.0002053262],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9334352,0.0001356817,0.06575542,0.000369596,0.0001432901,0.00006128853,0.00001109425,0.000008126421,0.00008031556],"genre_scores_gemma":[0.9870757,0.001329883,0.01149676,0.00001669431,0.00001721321,0.000001525702,0.00005582588,0.000003577662,0.000002761954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7665067,"threshold_uncertainty_score":0.2837703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05835315601025873,"score_gpt":0.3208497345865705,"score_spread":0.2624965785763117,"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."}}