{"id":"W4394974607","doi":"","title":"NUMEVIE : inclusion du numérique à tous les âges de la vie – Résultats préliminaires auprès de la population âgée (60 ans et plus)","year":2022,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Interdisciplinary Research in Rehabilitation","funders":"","keywords":"Humanities; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005964047,0.0008122423,0.002183018,0.00297647,0.001348443,0.002374995,0.002146435,0.001780557,0.009037105],"category_scores_gemma":[0.04167764,0.0006302765,0.002914566,0.002656834,0.0006719807,0.004474289,0.004608559,0.001512902,0.001749188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243064,"about_ca_system_score_gemma":0.003122509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03629888,"about_ca_topic_score_gemma":0.04570277,"domain_scores_codex":[0.9966323,0.001450306,0.0005202677,0.0004382422,0.0006622964,0.0002965335],"domain_scores_gemma":[0.9863145,0.006574595,0.001996148,0.0009579047,0.002939329,0.001217573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003294505,0.0007466924,0.9192445,0.002393342,0.001626676,0.0001876484,0.009277012,0.0002193054,0.0001997743,0.0007947423,0.004316656,0.05769908],"study_design_scores_gemma":[0.0003120727,0.00118085,0.9740573,0.00141132,0.001518583,0.0002323611,0.008992514,0.0008763672,0.0002055411,0.0009461269,0.01019074,0.00007612634],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758375,0.005473928,0.001098927,0.001116717,0.0006345866,0.0007788962,0.00833513,0.00004845746,0.006675825],"genre_scores_gemma":[0.9676508,0.003395756,0.004581906,0.000574327,0.0004752137,0.00517347,0.00604406,0.00006786841,0.01203666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03629888,"threshold_uncertainty_score":0.0721752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952307976981277,"score_gpt":0.3186418076124019,"score_spread":0.2991187278425891,"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."}}