{"id":"W4225808265","doi":"10.1002/trc2.12246","title":"AD Informer Set: Chemical tools to facilitate Alzheimer's disease drug discovery","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Translational Research & Clinical Interventions","topic":"Cholinesterase and Neurodegenerative Diseases","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium","funders":"National Institute on Aging; Genentech; National Institutes of Health; Ministero dello Sviluppo Economico; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Novartis Pharma; Canada Foundation for Innovation; Ontario Ministry of Economic Development and Innovation; Wellcome Trust; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Pfizer","keywords":"Set (abstract data type); Drug discovery; General partnership; Computer science; Disease; Computational biology; Portfolio; Alzheimer's disease; Dementia; Drug development; Bioinformatics; Data science; Medicine; Drug; Biology; Pharmacology; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004831847,0.00463328,0.003006488,0.01018334,0.001099985,0.004918758,0.003787069,0.002472223,0.1467025],"category_scores_gemma":[0.01129145,0.001447023,0.001811544,0.005755237,0.0005724863,0.003281841,0.00326757,0.002400626,0.08112554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001823733,"about_ca_system_score_gemma":0.004506529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00197903,"about_ca_topic_score_gemma":0.004221567,"domain_scores_codex":[0.9978125,0.0005620877,0.0002847664,0.0002421002,0.000963285,0.0001352694],"domain_scores_gemma":[0.9936669,0.003405458,0.0007917708,0.0007281766,0.0009719236,0.0004356843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001945575,0.0004062539,0.002307637,0.01337826,0.0004423806,0.0006790262,0.0002659364,0.004716594,0.01843345,0.01843639,0.7448093,0.1941793],"study_design_scores_gemma":[0.0005553881,0.0002188873,0.001423868,0.0008546482,0.000289371,0.0005038065,0.00005842309,0.005150046,0.01400181,0.009749946,0.967077,0.0001167298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004980531,0.009039974,0.07841285,0.003088693,0.0008245686,0.001937758,0.6834282,0.1301791,0.08810842],"genre_scores_gemma":[0.01892252,0.009534174,0.2275357,0.001686696,0.0004806487,0.00243665,0.712059,0.008039689,0.01930477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1467025,"threshold_uncertainty_score":0.4907688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5139029356923754,"score_gpt":0.5102189383388899,"score_spread":0.003683997353485569,"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."}}