{"id":"W2203637399","doi":"10.1016/j.dib.2015.11.062","title":"Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes","year":2015,"lang":"en","type":"article","venue":"Data in Brief","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; Hospital for Sick Children; University of Toronto","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of California, Santa Barbara; University of Toronto; Philipps-Universität Marburg; National Science Foundation; National Institutes of Health; Cancer Prevention and Research Institute of Texas","keywords":"Proteome; Computational biology; Data science; Bioinformatics; Biology; Computer science","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":[0.0008874983,0.001271004,0.00106426,0.004240453,0.001042208,0.001074098,0.001058177,0.001050828,0.005629809],"category_scores_gemma":[0.003297097,0.0003594465,0.0009218736,0.007397722,0.000350297,0.0006881206,0.001898485,0.0009982559,0.004948113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008102013,"about_ca_system_score_gemma":0.001831591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004755168,"about_ca_topic_score_gemma":0.01159087,"domain_scores_codex":[0.9991847,0.00009144301,0.00007887137,0.0003625457,0.0001985596,0.00008391051],"domain_scores_gemma":[0.9986572,0.0003534799,0.0002439135,0.0003024358,0.0002285609,0.0002143374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004081205,0.000571512,0.1560815,0.01925954,0.002474931,0.003019938,0.001295124,0.02146419,0.1671221,0.01665802,0.5344285,0.07354334],"study_design_scores_gemma":[0.0004346823,0.0002032286,0.3257059,0.0007370078,0.000760485,0.001669665,0.0005595338,0.01641739,0.02157534,0.01288941,0.6188956,0.0001516558],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02288949,0.0008663817,0.002316505,0.0001792236,0.00002585557,0.00004032889,0.9706561,0.001148959,0.00187721],"genre_scores_gemma":[0.01811611,0.000345958,0.004796187,0.00004536438,0.000008607877,0.0001089941,0.9762814,0.00007526015,0.0002220734],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005629809,"threshold_uncertainty_score":0.01883358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04670944098356348,"score_gpt":0.3073936541186142,"score_spread":0.2606842131350507,"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."}}