{"id":"W1970188140","doi":"10.1186/1477-5956-11-s1-s11","title":"The role of electrostatic energy in prediction of obligate protein-protein interactions","year":2013,"lang":"en","type":"article","venue":"Proteome Science","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Obligate; Curse of dimensionality; Discriminative model; Computer science; Support vector machine; Feature selection; Pattern recognition (psychology); Artificial intelligence; Biology","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":[0.001716188,0.0008122939,0.0007916311,0.003046982,0.0005435632,0.0008417214,0.000709283,0.0009138867,0.001102822],"category_scores_gemma":[0.00353238,0.0001143088,0.0007370461,0.001992205,0.0002759308,0.001067649,0.0007937545,0.0007641238,0.0006760725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004750472,"about_ca_system_score_gemma":0.000540354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002728739,"about_ca_topic_score_gemma":0.002503831,"domain_scores_codex":[0.9986911,0.000274399,0.0001786514,0.0003740388,0.0003609757,0.0001207865],"domain_scores_gemma":[0.9966331,0.001754626,0.0005685235,0.0003306786,0.0004782529,0.0002348882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001648255,0.001390286,0.619902,0.001165571,0.0006442291,0.0006375916,0.0001511913,0.08246612,0.02045584,0.001229365,0.01612982,0.2541797],"study_design_scores_gemma":[0.00007724603,0.0004302299,0.2362114,0.00009755132,0.0001544687,0.001120806,0.0001997095,0.7376453,0.01479267,0.004174919,0.005028418,0.00006741066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609757,0.004240189,0.02364528,0.000392093,0.00007244946,0.00008495968,0.007326113,0.001036565,0.002226816],"genre_scores_gemma":[0.9672537,0.0005744877,0.0185899,0.00006689179,0.00005050447,0.00004557706,0.01295102,0.0000314059,0.0004365472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003046982,"threshold_uncertainty_score":0.009076118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002827000605324953,"score_gpt":0.2104258324281014,"score_spread":0.2075988318227764,"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."}}