{"id":"W4399674474","doi":"10.3390/ijms25126535","title":"A Machine Learning Approach to Identify Key Residues Involved in Protein–Protein Interactions Exemplified with SARS-CoV-2 Variants","year":2024,"lang":"en","type":"article","venue":"International Journal of Molecular Sciences","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Key (lock); Computational biology; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Protein–protein interaction; Biology; Virology; Computer science; Genetics; Medicine; Infectious disease (medical specialty)","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":[0.0004546419,0.0005488498,0.000606749,0.0006872175,0.0005912557,0.000495158,0.0007765008,0.0008834212,0.0011762],"category_scores_gemma":[0.0009426366,0.000319449,0.0007144957,0.0004937102,0.0004016185,0.0005206788,0.0004380951,0.0008729725,0.0001813832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000635913,"about_ca_system_score_gemma":0.0009109483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003808819,"about_ca_topic_score_gemma":0.003540402,"domain_scores_codex":[0.9998869,0.00003948322,0.000007362545,0.00002430884,0.00002259566,0.00001932042],"domain_scores_gemma":[0.9997489,0.000133351,0.00003504301,0.0000234415,0.00003637837,0.00002292562],"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":[0.00009529579,0.0001719304,0.002334207,0.00007052396,0.0000890311,0.00007833161,0.00003993163,0.9604441,0.005441722,0.007331525,0.000430048,0.02347337],"study_design_scores_gemma":[0.000002988512,0.0000108325,0.000119102,0.000001111418,0.000002554289,0.000003730656,0.000002509287,0.9989408,0.0001885476,0.0006469632,0.00007945661,0.00000156279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.515379,0.0009546151,0.4745891,0.0008839054,0.0001277116,0.0002142129,0.0004446317,0.0009107585,0.006496083],"genre_scores_gemma":[0.8840011,0.0003795123,0.1127717,0.0001667799,0.00004521015,0.0003422194,0.0004032597,0.00005987202,0.001830333],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003808819,"threshold_uncertainty_score":0.007573307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04761203248464381,"score_gpt":0.3672062557005663,"score_spread":0.3195942232159225,"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."}}