{"id":"W4382933088","doi":"10.1155/2023/3226726","title":"Heterogeneity in the Preferences of Potential Users of Automated Transit Network (ATN)","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public transport; Multinomial logistic regression; Mixed logit; Transport engineering; Computer science; Transit (satellite); Order (exchange); Operations research; Logistic regression; Business; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001920792,0.000155461,0.0002374133,0.0004067842,0.0004894329,0.0009867102,0.0002989632,0.0004367014,0.003305117],"category_scores_gemma":[0.007745463,0.0001214644,0.0005111558,0.0006431919,0.0003652093,0.0007223709,0.0004512521,0.0005678412,0.0003461858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004972711,"about_ca_system_score_gemma":0.0003332356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006069877,"about_ca_topic_score_gemma":0.00723389,"domain_scores_codex":[0.9977464,0.001216354,0.0001384481,0.0001963191,0.000438293,0.0002640991],"domain_scores_gemma":[0.9959894,0.002164956,0.0009048901,0.0002848485,0.0004129213,0.0002429649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000215632,0.0002080587,0.9764618,0.00004468206,0.0001043755,0.0003042448,0.002781855,0.001345897,0.0005361072,0.001014114,0.0005473302,0.01643588],"study_design_scores_gemma":[0.00001924843,0.0003612617,0.9739636,0.00003955432,0.00007224213,0.0005713191,0.01249116,0.008449086,0.0003369645,0.001839808,0.001814134,0.00004156028],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981847,0.00004064879,0.0005100784,0.0001162613,0.000003146388,0.00001626653,0.0001048233,0.000001668779,0.001022443],"genre_scores_gemma":[0.9995986,0.00002057522,0.0001342802,0.00002410199,0.000002622755,0.000008073195,0.00005228874,5.302082e-7,0.0001589281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006069877,"threshold_uncertainty_score":0.01206911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198002590128574,"score_gpt":0.3032668108528709,"score_spread":0.2834665518400135,"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."}}