{"id":"W2141690555","doi":"10.1371/journal.pcbi.1000333","title":"BETASCAN: Probable β-amyloids Identified by Pairwise Probabilistic Analysis","year":2009,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"U.S. National Library of Medicine; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Pairwise comparison; BETA (programming language); Probabilistic logic; Sequence (biology); Protein folding; Protein structure; Protein structure prediction; Globular protein; Folding (DSP implementation); Multiple sequence alignment; Computational biology; Peptide sequence; Mathematics; Algorithm; Sequence alignment; Computer science; Artificial intelligence; Chemistry; Biology; Crystallography; Genetics; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009928872,0.0001621394,0.0003780968,0.0002251451,0.0001075747,0.00002323351,0.00009430476,0.00008237732,0.0003177809],"category_scores_gemma":[0.00009087971,0.0001308855,0.0001779043,0.0005757516,0.0001186272,0.0000557543,0.00002475567,0.0001121386,0.0001971329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009601583,"about_ca_system_score_gemma":0.0001969602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000197907,"about_ca_topic_score_gemma":0.000004985477,"domain_scores_codex":[0.9985965,0.0001044011,0.0002704525,0.000406199,0.0002816376,0.0003407543],"domain_scores_gemma":[0.9990658,0.0001443064,0.00007051443,0.0001922609,0.0002447817,0.0002823079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002777913,0.01900205,0.736403,0.0003022116,0.162651,0.0004917986,0.0003419084,0.01030595,0.005218508,0.02327622,0.02563091,0.01359849],"study_design_scores_gemma":[0.008733379,0.004503845,0.7508027,0.00009023745,0.01472477,0.00006481292,0.00004850684,0.06873126,0.00122993,0.1492003,0.0009655037,0.0009047645],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874365,0.003353035,0.002092844,0.003416789,0.00003979721,0.001114807,0.0002906429,0.0001874992,0.002068043],"genre_scores_gemma":[0.9936098,0.00001636567,0.001698701,0.0004585119,0.00005276032,0.0000550627,0.003963646,0.000008786721,0.0001362956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479263,"threshold_uncertainty_score":0.5337358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730463737018389,"score_gpt":0.3131610376567985,"score_spread":0.2858564002866146,"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."}}