{"id":"W6998844882","doi":"","title":"Between Old and New\\n Needs: The Issue of Inclusion of the Elderly before, during and after COVID-19.\\n The Case of Rural Areas in Canada-Québec and Italy","year":2024,"lang":"en","type":"article","venue":"Érudit (Université de Montréal)","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rural area; Vulnerability (computing); Context (archaeology); Inclusion (mineral); Pandemic; Variety (cybernetics); Public health; Social environment; Social vulnerability","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001579129,0.0003202848,0.0002908455,0.001116611,0.01627154,0.004753779,0.001282894,0.001653948,0.00228873],"category_scores_gemma":[0.002552465,0.0001874423,0.000313842,0.001388748,0.009316541,0.002276886,0.00628616,0.001458423,0.0001774097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02196437,"about_ca_system_score_gemma":0.02052093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7642567,"about_ca_topic_score_gemma":0.9025834,"domain_scores_codex":[0.9978277,0.0006642456,0.00004668845,0.00009975544,0.0002196943,0.001141778],"domain_scores_gemma":[0.9983021,0.000266092,0.0002596322,0.00004922846,0.0003163415,0.000806567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004882681,0.00005908432,0.03997179,0.0001040886,0.00001371196,0.003308999,0.9364548,0.00005370124,0.0003188526,0.004305658,0.003468169,0.0118923],"study_design_scores_gemma":[0.000001774814,0.00002358583,0.03030914,0.00008208956,0.000006856201,0.0003557578,0.957849,0.00002177099,0.00003497648,0.0002198652,0.01108435,0.00001081755],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723631,0.001360787,0.0001226937,0.009324967,0.00007957308,0.00003531195,0.00006619994,0.000004890726,0.01664254],"genre_scores_gemma":[0.9959458,0.0006567864,0.00008994409,0.0007222253,0.00002910474,0.0000125211,0.00002297236,0.000002905691,0.00251787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2357433,"threshold_uncertainty_score":0.4742633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007955101716455401,"score_gpt":0.2371419913158078,"score_spread":0.2291868895993524,"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."}}