{"id":"W4380871419","doi":"10.1186/s13195-023-01250-5","title":"Immediate word recall in cognitive assessment can predict dementia using machine learning techniques","year":2023,"lang":"en","type":"article","venue":"Alzheimer s Research & Therapy","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University; University of Northern British Columbia","funders":"","keywords":"Recall; Dementia; Cognition; Cognitive psychology; Artificial intelligence; Psychology; Word (group theory); Computer science; Machine learning; Natural language processing; Linguistics; Medicine; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005238515,0.0002993743,0.0004419576,0.001589449,0.0003747299,0.0001314391,0.0002877095,0.0001564286,0.001074709],"category_scores_gemma":[0.0002500397,0.0002594925,0.0001401964,0.00252412,0.0003537489,0.0001947726,0.0003280914,0.001947322,0.00009212377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001673349,"about_ca_system_score_gemma":0.0007758334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001752288,"about_ca_topic_score_gemma":0.0001987102,"domain_scores_codex":[0.994041,0.001249091,0.00048428,0.0007148829,0.002001006,0.001509734],"domain_scores_gemma":[0.9979206,0.0006065585,0.00007776258,0.0003152791,0.0006936447,0.0003862052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001196699,0.0006266427,0.6203336,0.00003573696,0.001757185,0.0005595742,0.0006621871,0.000001885162,0.05009095,0.00002355057,0.0004791866,0.3242329],"study_design_scores_gemma":[0.01060019,0.0047942,0.7995147,0.0009588696,0.0003580093,0.0000497927,0.002709999,0.006715257,0.1524298,0.0007296051,0.02043768,0.0007018584],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833175,0.005347084,0.0001381301,0.002452957,0.00008517825,0.003273024,0.00003007646,0.0003364352,0.005019601],"genre_scores_gemma":[0.9869774,0.009968155,0.0007699579,0.000252201,0.0002001565,0.0006703192,0.0003240738,0.0000937572,0.000743956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.323531,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1697013273415666,"score_gpt":0.4683237109864767,"score_spread":0.2986223836449101,"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."}}