{"id":"W2938392017","doi":"10.1101/605451","title":"A reference map of the human protein interactome","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; McGill University; McGill University Health Centre; Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Human Genome Research Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canadian Institutes of Health Research; National Research Foundation; Canada Excellence Research Chairs, Government of Canada; American Heart Association","keywords":"Interactome; Computational biology; Biology; Proteome; Context (archaeology); Alternative splicing; Phenotype; Function (biology); Human proteome project; Proteomics; Human genetics; Genetics; Gene; Exon","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003175716,0.0003509604,0.0003453376,0.00005780936,0.00008140902,0.00006755241,0.000946362,0.0005994504,0.00002710848],"category_scores_gemma":[0.00003688311,0.0002875331,0.0001850291,0.00008997554,0.0001267502,0.000005002205,0.001319345,0.0005933704,0.00003695522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004511621,"about_ca_system_score_gemma":0.0003366727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002047586,"about_ca_topic_score_gemma":0.000003521905,"domain_scores_codex":[0.9984065,0.0000760437,0.0005043279,0.0004860167,0.0002032005,0.0003239144],"domain_scores_gemma":[0.997291,0.000006546165,0.0005876869,0.001767777,0.0002612525,0.00008575916],"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":[0.00001310188,0.00004718653,0.001388606,0.0003969225,0.000107697,6.50875e-7,0.000004875464,0.00006928281,0.996146,0.0004661678,0.00135831,0.000001164583],"study_design_scores_gemma":[0.0005062665,0.0001262555,0.02419725,0.0007224343,0.00006580687,1.19587e-8,0.000003510709,0.0002236916,0.9366339,0.00001444558,0.03679026,0.0007161731],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968136,0.0005800157,0.0005796052,0.0001199803,0.0006960836,0.0009029588,0.0001912855,0.00002537137,0.00009107557],"genre_scores_gemma":[0.9985372,0.00002196482,0.0007904744,0.0001433588,0.0002731851,0.00008074106,0.000001602687,0.00005815561,0.00009329033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05951214,"threshold_uncertainty_score":0.9999577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179986039683922,"score_gpt":0.220594004342527,"score_spread":0.2087941439456878,"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."}}