{"id":"W4392507767","doi":"10.3389/fdgth.2024.1265846","title":"Multidimensional digital biomarker phenotypes for mild cognitive impairment: considerations for early identification, diagnosis and monitoring","year":2024,"lang":"en","type":"article","venue":"Frontiers in Digital Health","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Government of Alberta","keywords":"Biomarker; Identification (biology); Population; Computer science; Cognition; Medicine; Psychiatry; Biology","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":[0.01573291,0.001407158,0.00217522,0.003732183,0.001218929,0.005701811,0.002385827,0.002796533,0.006170942],"category_scores_gemma":[0.05523129,0.0006009091,0.001411819,0.00179842,0.003387642,0.008091506,0.003561137,0.005515657,0.001618466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002165536,"about_ca_system_score_gemma":0.005864569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005031991,"about_ca_topic_score_gemma":0.009987793,"domain_scores_codex":[0.9949384,0.002686305,0.0006367656,0.0004338456,0.001122398,0.000182307],"domain_scores_gemma":[0.9647616,0.01929234,0.00269135,0.002054464,0.009110685,0.002089597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007382189,0.0003585827,0.09756247,0.002773819,0.0003233395,0.0008978509,0.001560497,0.002300786,0.003058336,0.0563149,0.06077606,0.7733353],"study_design_scores_gemma":[0.000271506,0.001630217,0.1733816,0.02177449,0.001356557,0.01163753,0.009565498,0.02789428,0.005391328,0.4970629,0.2492163,0.0008176566],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.05480081,0.2980066,0.1752978,0.4293283,0.004892432,0.0009929938,0.003013212,0.001046356,0.03262147],"genre_scores_gemma":[0.4306808,0.1274922,0.3980764,0.02901879,0.005303635,0.002163346,0.002211887,0.0001962956,0.004856509],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01573291,"threshold_uncertainty_score":0.08320463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04010375472802818,"score_gpt":0.3575258662311606,"score_spread":0.3174221115031324,"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."}}