{"id":"W3037271262","doi":"10.1007/978-3-030-51517-1_12","title":"Personalized and Contextualized Persuasion System for Older Adults’ Physical Activity Promoting","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Persuasion; Context (archaeology); Computer science; Internet privacy; Psychology; Gerontology; Applied psychology; Social psychology; Medicine","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":[0.0003676639,0.0005830419,0.0003759328,0.0004475091,0.0002907488,0.000756819,0.0007144293,0.000882939,0.009780869],"category_scores_gemma":[0.0008083648,0.0001517729,0.0003910506,0.0001804792,0.0001466221,0.0006465667,0.0005407878,0.0005607645,0.002095122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001754606,"about_ca_system_score_gemma":0.0002723223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006096256,"about_ca_topic_score_gemma":0.0005861081,"domain_scores_codex":[0.9998436,0.00003558974,0.00001478538,0.00004823022,0.00004062217,0.00001711483],"domain_scores_gemma":[0.9997424,0.0001258908,0.00001214219,0.00002857663,0.00006549739,0.00002532483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00129678,0.001441615,0.002956575,0.001406058,0.0001650108,0.001718815,0.002937347,0.007487999,0.1571612,0.01242501,0.04826479,0.7627388],"study_design_scores_gemma":[0.0008169232,0.003484763,0.02057626,0.0005703016,0.001046052,0.004884314,0.001660867,0.3473985,0.1769288,0.02510621,0.4171153,0.0004117338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1441998,0.00399198,0.7512034,0.0008640465,0.0009353437,0.001002506,0.001106445,0.04953778,0.04715865],"genre_scores_gemma":[0.5650865,0.001188028,0.3741703,0.0006176593,0.0002187255,0.0006952058,0.00177463,0.000600086,0.05564885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009780869,"threshold_uncertainty_score":0.03272021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02249249274067046,"score_gpt":0.2784977796855441,"score_spread":0.2560052869448737,"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."}}