{"id":"W4321124255","doi":"10.1039/d2dd00091a","title":"Latent spaces for antimicrobial peptide design","year":2023,"lang":"en","type":"article","venue":"Digital Discovery","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Alliance de recherche numérique du Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Compute Canada","keywords":"Antimicrobial; Peptide; Antimicrobial peptides; Computational biology; Biology; Microbiology; Biochemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009804718,0.0001994499,0.0002540328,0.0001087367,0.0001937024,0.0003308768,0.0001753301,0.0001268204,0.0000343025],"category_scores_gemma":[0.00006881737,0.0001725051,0.0002162931,0.0001476641,0.0001954237,0.000929463,0.0001155387,0.0001008631,0.001291404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002127598,"about_ca_system_score_gemma":0.00005095285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001843788,"about_ca_topic_score_gemma":0.000002602469,"domain_scores_codex":[0.9989551,0.00002292348,0.0002009797,0.000306187,0.00002616705,0.0004886582],"domain_scores_gemma":[0.9994798,0.0002256718,0.00007430795,0.0001710754,0.00003135866,0.00001778097],"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":[0.000423719,0.000148433,0.001103242,0.00006614114,0.0002389812,0.00001394531,0.0002562639,0.0004243846,0.5397508,0.002713601,0.4515232,0.003337346],"study_design_scores_gemma":[0.004020418,0.0008111086,0.006433293,0.0002960861,0.0001274825,0.0001225933,0.00146483,0.00008867332,0.7851253,0.004217301,0.1956622,0.00163073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802561,0.0001609249,0.0123683,0.0006887388,0.001340584,0.0006539291,0.001388954,0.0004291368,0.002713282],"genre_scores_gemma":[0.9469752,0.00004858022,0.0001040919,0.0001927979,0.00007792517,0.00002700136,0.0008017282,0.00003466132,0.05173798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2558609,"threshold_uncertainty_score":0.9994862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661322039331922,"score_gpt":0.2377952894557104,"score_spread":0.2111820690623911,"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."}}