{"id":"W2428380121","doi":"10.1007/978-1-61779-295-3_15","title":"Bioinformatic Approach to Identify Chaperone Pathway Relationship from Large-Scale Interaction Networks","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Canada Research Chairs; University of Toronto","funders":"Canadian Institutes of Health Research; Genome Canada","keywords":"Chaperone (clinical); Computational biology; Co-chaperone; Protein folding; Folding (DSP implementation); Biology; Cell biology; Hsp90; Genetics; Gene; Medicine","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":[0.001537853,0.001509038,0.0009819757,0.003924486,0.00158313,0.001777546,0.002203279,0.0007013044,0.004029419],"category_scores_gemma":[0.005346856,0.000839022,0.001902619,0.003030803,0.0006070579,0.00159799,0.001392851,0.001954057,0.001332581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001399186,"about_ca_system_score_gemma":0.001981755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003227159,"about_ca_topic_score_gemma":0.004534144,"domain_scores_codex":[0.9991167,0.0002647149,0.00006427091,0.0002000812,0.000310257,0.0000439148],"domain_scores_gemma":[0.9979113,0.001199454,0.0002050469,0.0002539294,0.000346399,0.00008386809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004996774,0.0006636603,0.008541767,0.001650891,0.0009259205,0.001035226,0.0004395618,0.5403619,0.04700537,0.117695,0.01795667,0.2632244],"study_design_scores_gemma":[0.00004216293,0.00002898161,0.001058554,0.0000278609,0.00008311147,0.0001552553,0.00005325331,0.9227096,0.005027207,0.0632558,0.007526835,0.00003129631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007762231,0.0001335933,0.9828167,0.000238979,0.00002232224,0.0002781184,0.002448943,0.005290649,0.001008449],"genre_scores_gemma":[0.06944628,0.0002323625,0.9205279,0.0001164555,0.0000265762,0.0009494917,0.007617875,0.0004632995,0.0006198594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004029419,"threshold_uncertainty_score":0.01347977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370195434298061,"score_gpt":0.3458623293729234,"score_spread":0.3088427859431173,"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."}}