{"id":"W3024162593","doi":"10.1149/ma2020-01352474mtgabs","title":"Protein-Based Biosensor for Screening of Tau Aggregation Inhibitors, a Pharmaceutical Application","year":2020,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Tau protein; Chemistry; Protein aggregation; Drug discovery; Neurodegeneration; Biophysics; Surface protein; Alzheimer's disease; Nanotechnology; Biochemistry; Disease; Biology; Materials science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008501265,0.001255562,0.0009064155,0.001169395,0.0003370583,0.0006913534,0.001507747,0.002990976,0.001558183],"category_scores_gemma":[0.0007260052,0.0003480658,0.0006088269,0.0009515198,0.0003227862,0.000619906,0.0004542789,0.001313593,0.001540667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005682872,"about_ca_system_score_gemma":0.0003637098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004040283,"about_ca_topic_score_gemma":0.0005526798,"domain_scores_codex":[0.9987337,0.0002327945,0.00005526213,0.0003128622,0.0005926604,0.00007271543],"domain_scores_gemma":[0.9997512,0.00006759185,0.00005023024,0.00001969212,0.00008206617,0.0000292937],"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":[0.00005319143,0.00009567374,0.0002394051,0.0003082701,0.00001791109,0.00008930063,0.00001860439,0.0001876382,0.9875277,0.0003687166,0.0006735836,0.01042007],"study_design_scores_gemma":[0.0000241097,0.0006936264,0.001027566,0.00004207161,0.00004109835,0.0005759429,0.00002859812,0.008557195,0.9770346,0.0002972633,0.01165463,0.0000233418],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2729351,0.1284072,0.5584009,0.004389823,0.0030258,0.001670846,0.005323053,0.005372964,0.02047449],"genre_scores_gemma":[0.6964636,0.03481432,0.247552,0.002693893,0.0004567403,0.001049198,0.002251503,0.00008853665,0.01463024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002990976,"threshold_uncertainty_score":0.005212665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05249398238543862,"score_gpt":0.339031000032573,"score_spread":0.2865370176471344,"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."}}