{"id":"W1884027602","doi":"","title":"Interaction Networks as Scaffolds for Organizing and Interpreting Proteomes","year":2010,"lang":"en","type":"article","venue":"PubMed Central","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Computer science; Metadata; Cluster analysis; Biological network; Data mining; Proteome; Graph; Component (thermodynamics); Function (biology); Computational biology; Artificial intelligence; Bioinformatics; Theoretical computer science; Biology","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":[0.0002405496,0.0001039782,0.00008134406,0.00001696057,0.00009309511,0.00007585666,0.00008877639,0.0001445747,0.00001562695],"category_scores_gemma":[0.00006316334,0.00009753811,0.00004103349,0.00002666324,0.00003880872,0.000007321875,0.00007867154,0.0001002158,0.000001510372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001177117,"about_ca_system_score_gemma":0.00002707243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000547873,"about_ca_topic_score_gemma":0.00002701803,"domain_scores_codex":[0.9990855,0.000008602034,0.0001521047,0.0001672885,0.00003761838,0.0005489278],"domain_scores_gemma":[0.9996058,0.00001199477,0.00007119423,0.0001259939,0.0000268955,0.0001581016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006309096,0.0001294064,0.03847582,0.0002148617,0.0002874899,0.000002914644,0.001212119,0.0006352264,0.3278876,0.003693437,0.01098265,0.6158476],"study_design_scores_gemma":[0.00613954,0.001072304,0.087249,0.0001727694,0.0002434511,0.0005312421,0.001799375,0.1361867,0.3429203,0.003379077,0.4174867,0.002819557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833524,0.0001212822,0.01405668,0.0001712361,0.001106474,0.0005084804,0.000003836326,0.00001464905,0.0006649989],"genre_scores_gemma":[0.9968699,0.00003831761,0.001519608,0.0003043809,0.0009820996,0.00009598,0.00005054925,0.00001789185,0.0001212859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.613028,"threshold_uncertainty_score":0.3977489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004972551244009523,"score_gpt":0.2139205628359068,"score_spread":0.2089480115918973,"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."}}