{"id":"W2966831659","doi":"10.1017/s0714980819000059","title":"Pré-implantation de l’Accompagnement-citoyen personnalisé d’intégration communautaire (APIC): Adaptabilité, collaboration et financement, les déterminants d’une implantation réussie","year":2019,"lang":"en","type":"article","venue":"Canadian Journal on Aging / La Revue canadienne du vieillissement","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Réseau québécois de recherche sur le vieillissement; Université de Sherbrooke","keywords":"Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005183019,0.000416941,0.0002965474,0.001006324,0.002258033,0.003681824,0.0008602536,0.0008483314,0.01627029],"category_scores_gemma":[0.0150457,0.0002586293,0.0005815465,0.0007555161,0.001906806,0.001591071,0.00460616,0.001232476,0.001428608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003298688,"about_ca_system_score_gemma":0.008093593,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01650107,"about_ca_topic_score_gemma":0.01906874,"domain_scores_codex":[0.9951028,0.001840414,0.0002496668,0.0003543324,0.001321316,0.001131412],"domain_scores_gemma":[0.9868559,0.003356327,0.002044953,0.0009148322,0.002896755,0.003931169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007039951,0.001697163,0.4803745,0.0005032023,0.0001578099,0.001751238,0.1211265,0.0007102958,0.004615357,0.01211338,0.005347861,0.3708986],"study_design_scores_gemma":[0.00007676229,0.001779051,0.7783473,0.0009225299,0.000152047,0.00141874,0.1338511,0.001778109,0.002623336,0.004421253,0.07448329,0.0001464382],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745882,0.0007567913,0.003638083,0.00159112,0.0001239147,0.0001751542,0.00009909311,0.0000721587,0.01895543],"genre_scores_gemma":[0.9870977,0.0003044972,0.002111425,0.0001614414,0.00002526681,0.0001900821,0.00007122508,0.00002015495,0.01001815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9834989,"threshold_uncertainty_score":0.05442953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738737076865156,"score_gpt":0.278985987824019,"score_spread":0.2615986170553675,"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."}}