{"id":"W2980845730","doi":"10.1016/j.jalz.2019.08.136","title":"P4‐588: END‐TO‐END 3D‐CONVOLUTIONAL NEURAL NETWORK FOR PREDICTING CONVERSION FROM MILD COGNITIVE IMPAIRMENT TO ALZHEIMER'S DEMENTIA","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Dementia; Cognitive impairment; Convolutional neural network; Neuroimaging; Artificial intelligence; Cognition; Psychology; Audiology; Pattern recognition (psychology); Computer science; Neuroscience; Medicine; Disease; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004124063,0.0003943466,0.0003145298,0.00015788,0.0005603821,0.0001480787,0.0004330388,0.0001279948,0.002196594],"category_scores_gemma":[0.0000866261,0.0004248297,0.0001968153,0.0004683775,0.00009389585,0.0003730686,0.000255399,0.0002373992,0.001261576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002893316,"about_ca_system_score_gemma":0.0000875467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001815126,"about_ca_topic_score_gemma":0.00005254746,"domain_scores_codex":[0.9964589,0.0002206431,0.0006066113,0.001214907,0.0006675948,0.0008313172],"domain_scores_gemma":[0.9981984,0.0005309891,0.0002960038,0.0004211078,0.0001576984,0.0003958367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.007024046,0.002345435,0.1355825,0.00006550643,0.04663355,0.00004552998,0.005138764,0.008956176,0.4928201,0.004269901,0.1220097,0.1751088],"study_design_scores_gemma":[0.007371532,0.002150663,0.2087159,0.0002075276,0.02525874,0.00002720224,0.0008059794,0.06245498,0.6345282,0.0005830197,0.05584324,0.002053037],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621725,0.009485699,0.008156479,0.003017811,0.007849136,0.006646123,0.0007908132,0.0005489421,0.001332473],"genre_scores_gemma":[0.989591,0.00001216581,0.002946392,0.006299262,0.0005550118,0.000310352,0.0001958871,0.0000653401,0.00002457908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1730558,"threshold_uncertainty_score":0.9998204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145980898821827,"score_gpt":0.2741973757169501,"score_spread":0.2327375667287318,"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."}}