{"id":"W2564942951","doi":"10.1016/j.trci.2016.12.001","title":"Cross‐validation of optimized composites for preclinical Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Translational Research & Clinical Interventions","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Japan Science and Technology Agency; Genentech; H. Lundbeck A/S; Servier; Canadian Institutes of Health Research; Weston Brain Institute; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Takeda Pharmaceutical Company; AbbVie; Norman Cousins Center for Psychoneuroimmunology; Merck; GE Healthcare; BioClinica; Eli Lilly and Company; Michael J. Fox Foundation for Parkinson's Research","keywords":"Weighting; Cognition; Statistical power; Sample size determination; Cross-validation; Face validity; Computer science; Mathematics; Statistics; Artificial intelligence; Medicine; Psychometrics; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007155541,0.0002503088,0.0005999769,0.0004315634,0.0003419849,0.00009353792,0.0004190501,0.0001881367,0.005199996],"category_scores_gemma":[0.002438778,0.0001872519,0.001881549,0.0004255243,0.00137766,0.0004474163,0.0001561478,0.0004432994,0.0001631306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001681746,"about_ca_system_score_gemma":0.0005602992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001731248,"about_ca_topic_score_gemma":0.000007911511,"domain_scores_codex":[0.9934801,0.001041672,0.002263593,0.0008192606,0.001661203,0.0007341959],"domain_scores_gemma":[0.9894382,0.00612467,0.0002828967,0.0005671912,0.002833722,0.0007532791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01137672,0.008151731,0.8123242,0.0002066802,0.01807516,0.00001715512,0.00003552668,0.00002265928,0.002258834,0.008576131,0.003727535,0.1352276],"study_design_scores_gemma":[0.01756368,0.003408054,0.931731,0.001359248,0.01056571,0.000004857217,0.00002393549,0.001374436,0.01592913,0.007958832,0.009706718,0.0003743624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6312273,0.04913017,0.2487832,0.04702052,0.00127374,0.0148177,0.002589738,0.0003040149,0.004853649],"genre_scores_gemma":[0.9861413,0.0004255821,0.01103345,0.00009747733,0.0002916566,0.0007387581,0.000594345,0.00004965545,0.0006277837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.354914,"threshold_uncertainty_score":0.9957094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3548713531046037,"score_gpt":0.5604750576522419,"score_spread":0.2056037045476383,"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."}}