{"id":"W6893421361","doi":"10.5281/zenodo.16883495","title":"Recharging the 15-Minute City: How e-micromobility is expanding access","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Focus (optics); Data access; Government (linguistics); Key (lock); Current (fluid); Universal design","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":[0.002251412,0.0002256639,0.0002317845,0.0008276571,0.002327692,0.007801278,0.001264742,0.002098681,0.02020799],"category_scores_gemma":[0.005916002,0.0002392987,0.0004582782,0.001319383,0.005061605,0.01018535,0.007796876,0.001398213,0.001596757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002563736,"about_ca_system_score_gemma":0.001988305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033353,"about_ca_topic_score_gemma":0.01330986,"domain_scores_codex":[0.9979443,0.001151862,0.00004263896,0.0001775529,0.0002680491,0.0004156154],"domain_scores_gemma":[0.9975832,0.001162527,0.0001310764,0.0002594645,0.000324846,0.0005389099],"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":[0.0001874541,0.00009128322,0.006964432,0.0002472961,0.00002154287,0.0004924682,0.02425396,0.003223072,0.0009898467,0.8164524,0.02198561,0.1250906],"study_design_scores_gemma":[0.00003201613,0.000130655,0.008395374,0.0004650048,0.00002907625,0.0007143577,0.03909056,0.005022449,0.0007320556,0.3710679,0.5742518,0.000068817],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2860832,0.008959591,0.06314006,0.06651804,0.000917595,0.0001148491,0.000483412,0.0005285231,0.5732548],"genre_scores_gemma":[0.9752163,0.00207325,0.004173659,0.0008416527,0.0001410351,0.00004861777,0.00008724075,0.00009552763,0.01732277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02020799,"threshold_uncertainty_score":0.06760252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07594176110733426,"score_gpt":0.3348226999856983,"score_spread":0.2588809388783641,"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."}}