{"id":"W2128495797","doi":"10.1093/bioinformatics/btm068","title":"AMPer: a database and an automated discovery tool for antimicrobial peptides","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":233,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Antimicrobial peptides; Hidden Markov model; Construct (python library); Computer science; Computational biology; Biological database; Database; Biology; Artificial intelligence; Bioinformatics; Peptide; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002097084,0.001763187,0.001800917,0.004165852,0.0006907122,0.001665379,0.002584653,0.001991718,0.01431203],"category_scores_gemma":[0.007507848,0.0008268937,0.001124555,0.002832378,0.0004343975,0.002719712,0.001832031,0.001590574,0.01298497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004828113,"about_ca_system_score_gemma":0.001372176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006633938,"about_ca_topic_score_gemma":0.0006833894,"domain_scores_codex":[0.9991251,0.0001950491,0.0001478172,0.0002149171,0.0002483768,0.00006884241],"domain_scores_gemma":[0.9977756,0.001116649,0.0003656696,0.0002510135,0.0002587144,0.0002323825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005637241,0.0008369335,0.00896295,0.008578924,0.0004725037,0.003431696,0.0005771414,0.02434158,0.09235167,0.02106425,0.3194045,0.5143408],"study_design_scores_gemma":[0.001657009,0.001030381,0.01269617,0.001061359,0.0004185135,0.004592491,0.0003318086,0.1882742,0.09901717,0.0327141,0.6576998,0.0005069242],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.04604213,0.006572098,0.4066046,0.001474493,0.0004183456,0.001103832,0.2825943,0.2442807,0.01090947],"genre_scores_gemma":[0.06562638,0.003416018,0.5875309,0.0006134403,0.0001742339,0.001818325,0.3313207,0.005120314,0.004379651],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01431203,"threshold_uncertainty_score":0.0478785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418059534551134,"score_gpt":0.2691789252803353,"score_spread":0.254998329934824,"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."}}