{"id":"W2139652091","doi":"10.1111/j.1747-0285.2007.00543.x","title":"Evaluating Different Descriptors for Model Design of Antimicrobial Peptides with Enhanced Activity Toward <i>P. aeruginosa</i>","year":2007,"lang":"en","type":"article","venue":"Chemical Biology & Drug Design","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Antimicrobial; Peptide; Antimicrobial peptides; Quantitative structure–activity relationship; Pseudomonas aeruginosa; Computational biology; Predictive power; Molecular descriptor; Biological system; Computer science; Artificial intelligence; Combinatorial chemistry; Machine learning; Chemistry; Biology; Biochemistry; Microbiology; Physics; Bacteria","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001142955,0.0008510088,0.0007200622,0.0005360091,0.0001527969,0.0006932856,0.0005377805,0.0005916413,0.0006673253],"category_scores_gemma":[0.001933914,0.0002346335,0.0009351653,0.0003969332,0.0002513209,0.0004869502,0.0003676574,0.0004966927,0.0001653225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008226184,"about_ca_system_score_gemma":0.0009052326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00406694,"about_ca_topic_score_gemma":0.002562161,"domain_scores_codex":[0.9997652,0.0000885964,0.00001825099,0.00005159967,0.0000433233,0.00003299555],"domain_scores_gemma":[0.9991488,0.0006168846,0.00006488385,0.00003364323,0.0001113757,0.00002431569],"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":[0.00006154318,0.00005714112,0.0008668606,0.00003490509,0.00002706019,0.00001380649,0.000006157285,0.9903147,0.002860605,0.0003245426,0.00005218601,0.005380548],"study_design_scores_gemma":[0.000006968874,0.00005573375,0.0001241226,0.00000190989,0.00000984401,0.000003119844,0.00000236315,0.9980003,0.001587464,0.000125591,0.00007941786,0.000003241461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.746913,0.0007878569,0.2485995,0.0002657059,0.00004721726,0.0001646293,0.0006127039,0.0005201575,0.002089295],"genre_scores_gemma":[0.9663519,0.0002437294,0.03194639,0.00004606969,0.00001085926,0.0002415855,0.000582441,0.00002724436,0.0005498306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00406694,"threshold_uncertainty_score":0.008086562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05923480346162026,"score_gpt":0.2957971277811015,"score_spread":0.2365623243194812,"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."}}