{"id":"W2144506960","doi":"10.1002/psc.908","title":"QSAR modeling and computer‐aided design of antimicrobial peptides","year":2007,"lang":"en","type":"article","venue":"Journal of Peptide Science","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Quantitative structure–activity relationship; Antimicrobial; Peptide; Computational biology; Antimicrobial peptides; Molecular descriptor; Combinatorial chemistry; Biological system; Rational design; Computer science; Chemistry; Artificial intelligence; Machine learning; Biology; Nanotechnology; Biochemistry; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002728186,0.0001583515,0.0004028103,0.0004101922,0.0002620755,0.00004543312,0.0004253776,0.00009570145,0.00002036644],"category_scores_gemma":[0.0001353088,0.0001286605,0.0001061932,0.000295288,0.001276191,0.0006074234,0.0001384758,0.0002990877,0.000008373759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004200966,"about_ca_system_score_gemma":0.000227799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004923219,"about_ca_topic_score_gemma":0.00000412341,"domain_scores_codex":[0.9985139,0.00006386857,0.000679323,0.0002081268,0.0001127793,0.0004220405],"domain_scores_gemma":[0.9986658,0.0002015177,0.0005292928,0.0001461865,0.0003991413,0.00005806722],"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":[0.0001697874,0.00006238577,0.0005389141,0.00001941987,0.00003332317,0.00001162598,0.0005214117,0.00364036,0.9913977,0.0003372174,0.0007227676,0.002545105],"study_design_scores_gemma":[0.001456351,0.0007217213,0.002610455,0.0004152137,0.00006586377,0.001483455,0.001025057,0.003025841,0.9882488,0.0003553036,0.0002598205,0.0003321411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8191372,0.0003526881,0.1797197,0.00006721211,0.0005117034,0.00007664341,0.000003494631,0.000009287452,0.0001221262],"genre_scores_gemma":[0.9730065,0.0001381641,0.02651159,0.0001170924,0.0001026251,1.148791e-7,5.327853e-7,0.000009310618,0.0001141096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1538693,"threshold_uncertainty_score":0.5246622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243954307467711,"score_gpt":0.2528635603696819,"score_spread":0.2304240172950048,"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."}}