{"id":"W2962713877","doi":"10.1007/978-1-4939-9678-0_17","title":"Atomistic Simulation Tools to Study Protein Self-Aggregation","year":2019,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Amorfix (Canada); University of Toronto","funders":"","keywords":"Molecular dynamics; Protein aggregation; Peptide; Amyloid fibril; Chemistry; Biophysics; Amyloid (mycology); Observable; Protein structure; Computational biology; Amyloid β; Nanotechnology; Computer science; Disease; Biology; Computational chemistry; Materials science; Physics; Biochemistry; 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":[0.0006387767,0.0008028268,0.001250496,0.0007404527,0.001332516,0.000737268,0.001990804,0.001596957,0.004481791],"category_scores_gemma":[0.001906337,0.0006872781,0.0009140192,0.0009134689,0.0006466096,0.0006995618,0.001106434,0.002007945,0.0007771323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011831,"about_ca_system_score_gemma":0.001267599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004350727,"about_ca_topic_score_gemma":0.003691052,"domain_scores_codex":[0.9997173,0.00009369127,0.00001249989,0.00001733987,0.0001291973,0.00002992606],"domain_scores_gemma":[0.999126,0.0004527038,0.00005196166,0.0001362829,0.000155413,0.00007759576],"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":[0.00008164316,0.0002004171,0.0009877961,0.0002058886,0.000163877,0.0001467811,0.0001701947,0.9148207,0.006316405,0.06290981,0.003324045,0.01067239],"study_design_scores_gemma":[0.00003654587,0.00001189036,0.0001186294,0.00000801673,0.000009222819,0.00001499829,0.00001045624,0.9893063,0.0006578253,0.008060056,0.001757849,0.00000829895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1616683,0.00132326,0.7895217,0.001138631,0.0005585877,0.000488425,0.00161731,0.004315902,0.03936787],"genre_scores_gemma":[0.6415823,0.001531565,0.3448672,0.0004438196,0.0001422475,0.001749973,0.001282273,0.002059449,0.006341145],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004481791,"threshold_uncertainty_score":0.01499307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340638751197032,"score_gpt":0.3730310027432752,"score_spread":0.3596246152313049,"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."}}