{"id":"W2201698544","doi":"10.1371/journal.pone.0146127","title":"Using Human iPSC-Derived Neurons to Model TAU Aggregation","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"NIHR Newcastle Biomedical Research Centre; Innovative Medicines Initiative; Vlaamse regering; European Commission; Janssen Research and Development; National Institute for Health and Care Research; Alzheimer Society; Newcastle University; Alzheimer's Society; Medical Research Council; European Federation of Pharmaceutical Industries and Associations","keywords":"Tauopathy; Tau protein; Frontotemporal dementia; Hyperphosphorylation; Cell biology; Cellular model; Tau pathology; Neuroscience; Biology; Chemistry; Protein aggregation; Dementia; Phosphorylation; Cell culture; Alzheimer's disease; Neurodegeneration; Disease; Genetics; Medicine","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":[0.0003910454,0.0005911748,0.0005595883,0.0003962668,0.0002416412,0.0004653159,0.0004687472,0.0007702322,0.001294679],"category_scores_gemma":[0.0001725503,0.0001487607,0.0004608995,0.0003202302,0.0002865299,0.0002625295,0.0002906991,0.001237785,0.0006881305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003592156,"about_ca_system_score_gemma":0.000288454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008037496,"about_ca_topic_score_gemma":0.0008573426,"domain_scores_codex":[0.9997496,0.00002298924,0.00004142018,0.00005684158,0.00009567455,0.00003334524],"domain_scores_gemma":[0.9998958,0.00002370923,0.00002092801,0.00002138012,0.00002436633,0.00001377603],"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":[0.00009979854,0.0001187468,0.0001452431,0.0001853483,0.00002080602,0.0003142378,0.00007137247,0.0007756195,0.9944115,0.0005224588,0.000296766,0.003037942],"study_design_scores_gemma":[0.00002962979,0.0004384069,0.001217848,0.00003984934,0.00006867413,0.0005544145,0.00004169803,0.00247839,0.9861003,0.0002703637,0.008747826,0.00001273247],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9098054,0.006705666,0.05128871,0.0004437941,0.0005757854,0.00129661,0.01119488,0.0008762655,0.0178128],"genre_scores_gemma":[0.939199,0.006915282,0.03348802,0.0003106415,0.00005654112,0.001495491,0.00917231,0.0001624242,0.009200279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001294679,"threshold_uncertainty_score":0.004331112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3837831825718853,"score_gpt":0.3204733877169967,"score_spread":0.06330979485488863,"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."}}