{"id":"W2022134844","doi":"10.2174/092986611796378729","title":"3dswap-pred: Prediction of 3D Domain Swapping from Protein Sequence Using Random Forest Approach","year":2011,"lang":"en","type":"article","venue":"Protein and Peptide Letters","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre Hospitalier Universitaire de Québec; Wellcome Trust","keywords":"Sequence (biology); Random forest; Domain (mathematical analysis); Computer science; Limiting; Protein structure; Computational biology; Protein sequencing; Protein domain; Data mining; Web server; Algorithm; Artificial intelligence; Biology; Peptide sequence; Mathematics; Genetics; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001800857,0.001419746,0.001217744,0.002660615,0.0006054377,0.000647318,0.0009781353,0.001239596,0.002179055],"category_scores_gemma":[0.002176478,0.0005154482,0.002024856,0.001200447,0.0002451805,0.000901949,0.0006083472,0.001199139,0.001934687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004042963,"about_ca_system_score_gemma":0.0009089438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002552891,"about_ca_topic_score_gemma":0.003666684,"domain_scores_codex":[0.9992242,0.0001881194,0.00006230589,0.0002565854,0.0001533328,0.0001155523],"domain_scores_gemma":[0.9990439,0.0005255573,0.0001162535,0.00007324399,0.0001709072,0.00007013889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002184816,0.001245934,0.04776047,0.001595414,0.0007974541,0.001476753,0.0002131963,0.3280744,0.05004263,0.002658394,0.06341236,0.5005381],"study_design_scores_gemma":[0.00008613477,0.0001859193,0.004420989,0.00004136612,0.00006416345,0.0003765446,0.00003261901,0.9820666,0.007220117,0.001810274,0.00366265,0.00003257816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3274043,0.002732752,0.6058287,0.0005176812,0.0002543655,0.0006120455,0.02030723,0.03929058,0.0030524],"genre_scores_gemma":[0.48687,0.0008213442,0.466803,0.0001945122,0.00008367757,0.0006073451,0.0419226,0.000718042,0.001979553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002660615,"threshold_uncertainty_score":0.009523928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02626955349968676,"score_gpt":0.2242932271332879,"score_spread":0.1980236736336011,"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."}}