{"id":"W3004621076","doi":"10.4000/cybergeo.34011","title":"Réduire les usages de l’automobile en ville : une comparaison des débats médiatiques sur la réduction de la vitesse à 30 km/h à Paris et à Montréal","year":2020,"lang":"fr","type":"article","venue":"Cybergeo","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00151998,0.0003349711,0.0004678036,0.00004478777,0.0006009969,0.0002354649,0.0003710644,0.000498148,0.001124678],"category_scores_gemma":[0.0003245961,0.0003490974,0.0002291445,0.0006906529,0.001175347,0.0008681197,0.00006629492,0.0005711998,0.00007105213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002678241,"about_ca_system_score_gemma":0.0004563534,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1891121,"about_ca_topic_score_gemma":0.02512667,"domain_scores_codex":[0.9962882,0.001667761,0.0004540957,0.000541753,0.0003531331,0.0006950988],"domain_scores_gemma":[0.9980969,0.0009474615,0.0002003402,0.0002200149,0.0001142353,0.0004209917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008212874,0.0007989478,0.790319,0.0002825477,0.0001361632,0.0001093736,0.1340932,0.00149559,0.001971299,0.005674347,0.02058175,0.04445563],"study_design_scores_gemma":[0.0004685484,0.0001020718,0.5867817,0.00014705,0.0001492494,0.000003639925,0.005026328,0.001753937,0.00241891,0.002709297,0.3999638,0.000475478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951287,0.02193838,0.0007822711,0.0114597,0.0002538008,0.0002676214,0.0001144601,0.0002628183,0.01363396],"genre_scores_gemma":[0.9906961,0.004744173,0.0009368135,0.0004280845,0.0006280588,0.00004240109,0.0000483582,0.00004081562,0.002435197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3793821,"threshold_uncertainty_score":0.9998961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02855566318356744,"score_gpt":0.3214611893121818,"score_spread":0.2929055261286144,"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."}}