{"id":"W4409458628","doi":"10.1016/j.tre.2025.104126","title":"Emerging AI-driven smart and sustainable mobility","year":2025,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Business; Computer science; Engineering; Transport 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001042432,0.0002455965,0.0004033326,0.0003114297,0.0003665843,0.00006459553,0.0001218132,0.0001225129,0.0001615066],"category_scores_gemma":[0.00005656255,0.0002557499,0.00007379748,0.001209198,0.0003137559,0.0002703702,0.000002181511,0.0004741792,0.000005982704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004280692,"about_ca_system_score_gemma":0.0001115859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002015723,"about_ca_topic_score_gemma":0.001706967,"domain_scores_codex":[0.9977179,0.00007323736,0.0008754954,0.0004263236,0.0003817783,0.0005252393],"domain_scores_gemma":[0.9985945,0.0001760276,0.00005190448,0.0002869176,0.0007270519,0.0001635482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000477852,0.0002331257,0.06309661,0.03170286,0.0002570232,0.00006767802,0.001005984,0.006380155,0.0002165522,0.8701547,0.01106181,0.01577567],"study_design_scores_gemma":[0.001009039,0.00007667065,0.5331457,0.001860955,0.0003320792,7.694729e-7,0.0008181329,0.002339058,0.0001427211,0.007848059,0.451917,0.0005098679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3750313,0.1599544,0.4075275,0.02255712,0.001302336,0.01457381,0.002636462,0.002745891,0.01367111],"genre_scores_gemma":[0.9230618,0.07354889,0.000588715,0.000634814,0.00001869356,0.0004428241,0.001092159,0.00002849615,0.0005836373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8623067,"threshold_uncertainty_score":0.9999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04357292873988734,"score_gpt":0.3624839862421341,"score_spread":0.3189110575022467,"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."}}