{"id":"W3042249111","doi":"10.1212/wnl.0000000000010256","title":"Multitracer model for staging cortical amyloid deposition using PET imaging","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institute for Health and Care Research; Canadian Institutes of Health Research; ZonMw","keywords":"Amyloid (mycology); Pathology; Medicine; Deposition (geology); Neuroimaging; Nuclear medicine; Neuroscience; Psychology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00582036,0.001774446,0.001512992,0.001799726,0.0007508712,0.00163089,0.002285908,0.00150879,0.002322575],"category_scores_gemma":[0.007501942,0.0007658945,0.002763502,0.0008322587,0.000865566,0.0008783131,0.001117595,0.001487561,0.0007527239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001724191,"about_ca_system_score_gemma":0.001622619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02723028,"about_ca_topic_score_gemma":0.01438976,"domain_scores_codex":[0.9986227,0.0006551491,0.00005409064,0.0003640003,0.0001258925,0.000178166],"domain_scores_gemma":[0.9967224,0.00210492,0.0004161617,0.0002011993,0.0004055354,0.0001498245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006091124,0.0002122738,0.03202086,0.00007846271,0.0004918415,0.0002115487,0.0001411914,0.9331713,0.001828143,0.002844592,0.001337757,0.02705297],"study_design_scores_gemma":[0.0000302169,0.00008385671,0.002646565,0.00001096532,0.00005720718,0.00005301002,0.0000164248,0.994673,0.0001498998,0.002032365,0.0002288309,0.000017753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4162618,0.00110085,0.5736957,0.001219526,0.0001564214,0.0007318361,0.002254565,0.001501912,0.003077466],"genre_scores_gemma":[0.9153137,0.0003347158,0.07665965,0.0002937955,0.0001285254,0.0009315364,0.001911854,0.0001429599,0.004283318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02723028,"threshold_uncertainty_score":0.05414361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04642719828921936,"score_gpt":0.3452685152505768,"score_spread":0.2988413169613574,"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."}}