{"id":"W2101763464","doi":"10.1093/bioinformatics/bts072","title":"The identification of short linear motif-mediated interfaces within the human interactome","year":2012,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Interactome; Motif (music); Identification (biology); Computer science; Computational biology; Biology; Genetics; Gene; Ecology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009460085,0.0001306747,0.0001089287,0.00002561699,0.000220471,0.00005474103,0.0004249961,0.00009602784,0.000003697795],"category_scores_gemma":[0.0001058662,0.00007266288,0.00006981165,0.00009004677,0.0001849212,0.00002177822,0.0001774585,0.0001365825,0.00003351178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001128236,"about_ca_system_score_gemma":0.00002616511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003827504,"about_ca_topic_score_gemma":0.00001120201,"domain_scores_codex":[0.9987085,0.00002891065,0.0008175595,0.0000587761,0.00015337,0.000232914],"domain_scores_gemma":[0.9989532,0.0000422232,0.0003634551,0.0004899045,0.00009357496,0.00005762817],"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":[0.0002392333,0.0004869735,0.02252141,0.0005857939,0.001292515,4.119918e-7,0.02607296,0.001931199,0.8332724,0.01017708,0.05437403,0.04904601],"study_design_scores_gemma":[0.001211906,0.0006633772,0.01780897,0.0001454677,0.0002261599,0.00007411512,0.01627618,0.1460597,0.6708758,0.0007037518,0.1446922,0.001262326],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879518,0.0006122329,0.007972377,0.0001491937,0.0007674096,0.0003731138,0.00003858202,0.00001643682,0.002118899],"genre_scores_gemma":[0.998556,0.00009218497,0.0005708435,0.0001664,0.0001776912,0.00001192815,0.0001382086,0.00001137188,0.0002753861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1623965,"threshold_uncertainty_score":0.2963106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438794649319176,"score_gpt":0.2640914391990048,"score_spread":0.249703492705813,"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."}}