{"id":"W2170233798","doi":"10.1002/pmic.201100597","title":"Computational structural analysis of protein interactions and networks","year":2012,"lang":"en","type":"review","venue":"PROTEOMICS","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"Structural biology; Systems biology; Computational biology; Protein–protein interaction; Key (lock); Focus (optics); Modelling biological systems; Protein Interaction Networks; Computer science; Biology; Data science; Physics; Cell biology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00127923,0.001291757,0.002021093,0.002328564,0.0003135486,0.001291589,0.002321832,0.0007996788,0.001545906],"category_scores_gemma":[0.003728444,0.0006537118,0.001243992,0.002383734,0.0007864229,0.001553033,0.001129546,0.001406786,0.001234357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008424789,"about_ca_system_score_gemma":0.001027087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001863539,"about_ca_topic_score_gemma":0.002386259,"domain_scores_codex":[0.9994825,0.0001403626,0.00003236215,0.0001248389,0.0001936433,0.00002620982],"domain_scores_gemma":[0.9984382,0.001137443,0.00009480701,0.00009954649,0.0001942446,0.00003573108],"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":[0.0000707203,0.000104647,0.001979612,0.005802989,0.0008578895,0.000247927,0.00006505702,0.2371643,0.004336246,0.0584814,0.01991331,0.6709759],"study_design_scores_gemma":[0.00006400698,0.00007626917,0.002859567,0.001326918,0.0003807403,0.001020486,0.00007758218,0.6121019,0.007109744,0.2231502,0.1517108,0.0001218196],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01307216,0.4496158,0.5187644,0.00389704,0.0005514104,0.0001475312,0.002598562,0.002544332,0.008808839],"genre_scores_gemma":[0.1006936,0.5792521,0.3073203,0.0005554607,0.0009121368,0.0003659856,0.006917727,0.0004503436,0.003532377],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002328564,"threshold_uncertainty_score":0.006765306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064752393204088,"score_gpt":0.2963718297303511,"score_spread":0.2757243057983103,"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."}}