{"id":"W2982510473","doi":"10.3917/gs1.160.0015","title":"La mobilité d’aînés d’un arrondissement montréalais : frictions et ancrages","year":2019,"lang":"fr","type":"article","venue":"Gérontologie et société","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Humanities; Political science; Art","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002132352,0.000442082,0.0006458141,0.0000605202,0.0005506168,0.0001680218,0.0007202982,0.0006998145,0.01161897],"category_scores_gemma":[0.0001878549,0.0004335247,0.0004816376,0.0004463321,0.0008083397,0.001019592,0.000127981,0.0008345927,0.0006572393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004725155,"about_ca_system_score_gemma":0.0004397153,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01096704,"about_ca_topic_score_gemma":0.0244265,"domain_scores_codex":[0.9956749,0.001183926,0.0006474222,0.0009045348,0.0006058821,0.0009833084],"domain_scores_gemma":[0.9975885,0.00099646,0.000293205,0.000725788,0.0001337571,0.0002623348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004993991,0.001559829,0.8005182,0.0002138873,0.0003286069,0.00004197871,0.04062833,0.0001254465,0.0001467723,0.05939649,0.01154421,0.08544627],"study_design_scores_gemma":[0.0009257448,0.0001706231,0.7127418,0.00008704564,0.0001918622,0.000001649564,0.03724662,0.00007384475,0.0001022169,0.01721477,0.2306002,0.0006436871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7564254,0.01339596,0.000331244,0.0196249,0.003876104,0.0008103432,0.0001130605,0.0002979104,0.205125],"genre_scores_gemma":[0.9649405,0.002733758,0.0008573403,0.0009323394,0.0002303309,0.0001097171,0.00005135614,0.00003583345,0.03010877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.219056,"threshold_uncertainty_score":0.9998116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02992775539322937,"score_gpt":0.3568873317798514,"score_spread":0.326959576386622,"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."}}