{"id":"W7117353561","doi":"10.1002/alz70858_107291","title":"Using Machine Learning to Identify Features from Home Sensors that Predict Care Partner Burden","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Bruyère; University of Ottawa","funders":"","keywords":"Work (physics); Activity recognition; Outcome (game theory); Activities of daily living; Data collection","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":[0.001404542,0.001077089,0.0005701263,0.001822874,0.0003168535,0.0008231837,0.0004080425,0.0005571526,0.00105678],"category_scores_gemma":[0.005724156,0.0001906251,0.0007828779,0.0008364474,0.000238836,0.0005319744,0.0005023446,0.0007684441,0.0004194389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005247674,"about_ca_system_score_gemma":0.0005715458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004290974,"about_ca_topic_score_gemma":0.002879405,"domain_scores_codex":[0.9995469,0.0001448394,0.00003668398,0.0001315473,0.00007758834,0.00006240394],"domain_scores_gemma":[0.9982273,0.001134272,0.000197242,0.0001168716,0.0002623152,0.00006202994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007489688,0.001103581,0.4865723,0.0001078758,0.000598278,0.0002859341,0.0002814171,0.1955831,0.006750543,0.0005001153,0.002732114,0.3047357],"study_design_scores_gemma":[0.00001991241,0.0001730882,0.06174092,0.00002451642,0.00006623829,0.00009729918,0.0001055378,0.934468,0.001872127,0.001107441,0.0003036176,0.00002125549],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8961135,0.0002426096,0.1001404,0.0002985857,0.00004102572,0.0001520295,0.0008243326,0.0005370412,0.001650471],"genre_scores_gemma":[0.9830673,0.00005532036,0.015667,0.00003945192,0.00001537699,0.00007777902,0.0007332264,0.00001127999,0.0003331322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004290974,"threshold_uncertainty_score":0.008531988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04025460769926928,"score_gpt":0.3639804138229706,"score_spread":0.3237258061237014,"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."}}