{"id":"W1966395677","doi":"10.1016/j.jalz.2014.05.078","title":"IC‐P‐073: DISSIMILARITY BASED EXTRACTION OF COVARIANCE LINKED NETWORK (DECLINE) FEATURES FOR EARLY DETECTION OF AD","year":2014,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Entorhinal cortex; Precuneus; Covariance; Cognitive decline; Dementia; Neuroscience; Pattern recognition (psychology); Cortex (anatomy); Computer science; Artificial intelligence; Cognition; Psychology; Disease; Hippocampus; Medicine; Mathematics; Pathology; Statistics","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":[0.0006521766,0.0009922718,0.0007161386,0.00194555,0.0004040966,0.0006329818,0.0007370271,0.0009084546,0.001768742],"category_scores_gemma":[0.002708301,0.000195238,0.000658602,0.001399355,0.0002967015,0.0007497622,0.0009417363,0.000727584,0.0007768369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006113522,"about_ca_system_score_gemma":0.0005860404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004006134,"about_ca_topic_score_gemma":0.005885921,"domain_scores_codex":[0.9996656,0.00005316976,0.00002032951,0.00007863333,0.0001296741,0.00005249261],"domain_scores_gemma":[0.9994691,0.0001495478,0.0001004589,0.00008466542,0.0001497522,0.00004645436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001263866,0.0005859198,0.027719,0.0002737443,0.000371102,0.0008424774,0.0001907608,0.2102541,0.105996,0.009330579,0.02623786,0.6169346],"study_design_scores_gemma":[0.00002616887,0.0001276204,0.01297513,0.00001090525,0.00003197434,0.0003039812,0.00002876325,0.965259,0.01089449,0.006310413,0.004000131,0.00003145672],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1631343,0.0005343845,0.8256886,0.0003924611,0.0001112664,0.00029504,0.004464547,0.00280054,0.00257882],"genre_scores_gemma":[0.6515316,0.000321566,0.3307251,0.0001730218,0.0001650759,0.000404228,0.01152205,0.000306197,0.004851135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004006134,"threshold_uncertainty_score":0.007965684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04527630014342966,"score_gpt":0.2947215330200927,"score_spread":0.2494452328766631,"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."}}