{"id":"W4225852862","doi":"10.7717/peerj.13016","title":"Functional network motifs defined through integration of protein-protein and genetic interactions","year":2022,"lang":"en","type":"article","venue":"PeerJ","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biological network; Computational biology; Identification (biology); Systems biology; Bottleneck; Network motif; Gene regulatory network; Context (archaeology); Biology; Network analysis; Computer science; Interaction network; Gene; Genetics","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":[0.00009424755,0.0000888001,0.00009457286,0.00001774437,0.0001585786,0.0000131589,0.0000749262,0.00003901821,0.0001379651],"category_scores_gemma":[0.00001704706,0.00008863108,0.00005071404,0.00007514621,0.00004073732,0.000004474947,0.0001569323,0.0001208864,0.000002822371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001390858,"about_ca_system_score_gemma":0.00003813387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003144606,"about_ca_topic_score_gemma":0.00003506375,"domain_scores_codex":[0.999377,0.00003611599,0.0002078537,0.0001468729,0.0001024549,0.0001296993],"domain_scores_gemma":[0.9996413,0.000006397433,0.0001081949,0.0001689183,0.000047778,0.00002743996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002982724,0.0001297694,0.0005514348,0.00005214494,0.0001430404,0.000002114108,0.0003247474,0.02008115,0.9277687,0.007729063,0.01926696,0.02365257],"study_design_scores_gemma":[0.005355823,0.0040445,0.04226988,0.0001779775,0.0002411061,0.0005088037,0.002240154,0.06460438,0.2269345,0.0662621,0.5853176,0.002043163],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9234338,0.0009553072,0.07280533,0.0004439536,0.0002752206,0.0003927961,0.00003717973,0.00001102255,0.001645338],"genre_scores_gemma":[0.9880259,0.0000154811,0.009667519,0.0001409819,0.0002083342,0.0001100317,0.0001976389,0.00001107216,0.001623008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7008342,"threshold_uncertainty_score":0.3614271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0134225400745556,"score_gpt":0.2261866447356655,"score_spread":0.2127641046611099,"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."}}