{"id":"W4395686010","doi":"10.1016/j.jtbi.2024.111814","title":"A<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si33.svg\" display=\"inline\" id=\"d1e613\"><mml:mi>β</mml:mi></mml:math>-protein polymerization in Alzheimer disease: Optimal control for nucleation parameter estimation","year":2024,"lang":"en","type":"article","venue":"Journal of Theoretical Biology","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Providence Health Care","keywords":"Nucleation; Polymerization; Monomer; Cascade; Amyloid (mycology); Computer science; Mathematics; Algorithm; Chemistry; Biological system; Biology; Physics; Thermodynamics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008347525,0.001245216,0.0007361654,0.001585345,0.0006826235,0.002664117,0.002331898,0.001828931,0.5647202],"category_scores_gemma":[0.005475417,0.0008043828,0.001020727,0.001655641,0.0004078378,0.00249518,0.001274473,0.00167587,0.3082931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126502,"about_ca_system_score_gemma":0.0009798608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006169048,"about_ca_topic_score_gemma":0.006416869,"domain_scores_codex":[0.9994667,0.00009402757,0.00004779112,0.0001192297,0.0002297612,0.00004257656],"domain_scores_gemma":[0.9976184,0.0008685454,0.00013455,0.0004342847,0.000817704,0.0001264791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001452718,0.00007265934,0.0003263105,0.0003798986,0.00002428265,0.00008796561,0.00006230478,0.003493464,0.003924712,0.04097655,0.8733569,0.07714982],"study_design_scores_gemma":[0.0001397052,0.00003499656,0.001073775,0.0001432907,0.00001478313,0.0001972843,0.00004427314,0.06333671,0.01672162,0.04436042,0.8738581,0.00007504372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002402341,0.0004228175,0.5442238,0.004460148,0.001768436,0.0003326201,0.1077668,0.1329931,0.2056299],"genre_scores_gemma":[0.05212805,0.001361132,0.3743588,0.002696205,0.001072824,0.001252091,0.1226429,0.1049887,0.3394993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5647202,"threshold_uncertainty_score":0.6208738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686920550239777,"score_gpt":0.2965389100304614,"score_spread":0.2796697045280636,"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."}}