{"id":"W3151426590","doi":"10.1257/aer.20181662","title":"Mobility and Congestion in Urban India","year":2023,"lang":"en","type":"article","venue":"American Economic Review","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"TRIPS architecture; Reliability (semiconductor); Service (business); Traffic congestion; Econometrics; Computer science; Economics; Transport engineering; Economy; Engineering; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005675953,0.0002297031,0.000227987,0.001578384,0.0003571804,0.001187667,0.000507964,0.0002452981,0.001114141],"category_scores_gemma":[0.003316717,0.0002078248,0.0003900097,0.003228624,0.0007325104,0.0005718076,0.001025867,0.0004412619,0.0001131948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366806,"about_ca_system_score_gemma":0.0009218213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07034595,"about_ca_topic_score_gemma":0.03898247,"domain_scores_codex":[0.9996327,0.0001821577,0.00002060236,0.00004995463,0.00005643756,0.00005807164],"domain_scores_gemma":[0.9990596,0.000390823,0.0002749824,0.0000796607,0.0001548292,0.00004007571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008501793,0.00005758079,0.4146741,0.0003786841,0.0004395905,0.000387772,0.001242837,0.388207,0.0004597012,0.126999,0.006100655,0.06096809],"study_design_scores_gemma":[0.0000233523,0.0001250113,0.6844249,0.0001786383,0.0003141414,0.0003773085,0.002769443,0.2313685,0.0003442281,0.0607874,0.01919218,0.00009491057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9180402,0.005540792,0.03913012,0.003332378,0.000143807,0.00008140111,0.00337654,0.0002292319,0.0301256],"genre_scores_gemma":[0.9970406,0.0008993162,0.001308023,0.00003571562,0.00002808427,0.00002070611,0.0002532971,0.000004912067,0.0004095162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07034595,"threshold_uncertainty_score":0.139873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240631135996114,"score_gpt":0.3265269694892854,"score_spread":0.3024638558896741,"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."}}