{"id":"W4281825999","doi":"10.3390/ijerph19127130","title":"The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China","year":2022,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Natural Science Foundation of China","keywords":"Beijing; Public transport; Context (archaeology); Mixed logit; Travel behavior; Preference; Mode choice; China; Sharing economy; Business; Geography; Economics; Transport engineering; Computer science; Logistic regression; Microeconomics; Engineering","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":[0.001743288,0.0005615352,0.000613115,0.0009956635,0.002946537,0.0009227747,0.001264866,0.00111765,0.001955939],"category_scores_gemma":[0.002605923,0.0003330891,0.0008659022,0.001797202,0.001199863,0.0008845702,0.001599009,0.001099268,0.0001497398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006511863,"about_ca_system_score_gemma":0.00410393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2158627,"about_ca_topic_score_gemma":0.3050291,"domain_scores_codex":[0.9984183,0.0006981055,0.00007002235,0.000132306,0.0001608581,0.0005203889],"domain_scores_gemma":[0.9985167,0.0004212749,0.0002510716,0.0001343679,0.0001949385,0.0004815503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002235058,0.001517614,0.9241869,0.0001620177,0.0001772066,0.02047463,0.03235697,0.002259635,0.0009740485,0.001336898,0.001012308,0.01531837],"study_design_scores_gemma":[0.00004681766,0.000933419,0.8845973,0.00008028535,0.0001281552,0.003018858,0.09504689,0.01267086,0.0004779598,0.0008037571,0.002091216,0.0001043816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994616,0.00003691288,0.00007589461,0.00009372422,0.000001675832,0.00001822732,0.00002787112,0.000001337102,0.0002827076],"genre_scores_gemma":[0.9992796,0.00008471994,0.0001525382,0.00003155788,0.000002602165,0.00002280233,0.00004934112,0.00000179663,0.0003750476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2158627,"threshold_uncertainty_score":0.4292125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.136495595742205,"score_gpt":0.5018501689522465,"score_spread":0.3653545732100416,"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."}}