{"id":"W4408693799","doi":"10.1186/s13321-025-00979-5","title":"An interpretable deep geometric learning model to predict the effects of mutations on protein–protein interactions using large-scale protein language model","year":2025,"lang":"en","type":"article","venue":"Journal of Cheminformatics","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children’s Health Research Institute; Lawson Health Research Institute; University of Manitoba; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Scale (ratio); Artificial intelligence; Machine learning","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":[0.0005691525,0.0001895864,0.0002705109,0.0003523517,0.000154773,0.0000631959,0.0004382721,0.0001191263,0.000005052233],"category_scores_gemma":[0.001374512,0.0001436012,0.0001457237,0.0004054539,0.00004316569,0.00006540283,0.0001440565,0.0005619621,0.000002009928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006539605,"about_ca_system_score_gemma":0.0001922876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003918121,"about_ca_topic_score_gemma":0.000003511548,"domain_scores_codex":[0.9984952,0.00003715788,0.0008037224,0.00009088867,0.0003244444,0.0002485732],"domain_scores_gemma":[0.9984716,0.00004912352,0.0007020334,0.0003655113,0.000311029,0.0001007634],"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":[0.00009980873,0.0001256433,0.00006017326,0.0004717925,0.00008713307,6.22236e-7,0.004055362,0.5207611,0.4722017,0.00004938801,0.0001081046,0.001979169],"study_design_scores_gemma":[0.0003563969,0.0003187895,0.00001073802,0.0004149175,0.00004478027,0.000009449468,0.0008511692,0.6234721,0.37425,0.00005640056,0.0001238337,0.00009138699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.605496,0.0000392395,0.3925684,0.00003938149,0.00003581811,0.0004234482,0.000006701992,0.000007678932,0.00138322],"genre_scores_gemma":[0.9419887,0.000003115225,0.05682559,0.0001534932,0.00004616778,0.0000299861,0.00001954011,0.0000179821,0.0009154473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3364926,"threshold_uncertainty_score":0.5855888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004592795866963382,"score_gpt":0.2806849373223361,"score_spread":0.2760921414553727,"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."}}