{"id":"W4250616341","doi":"10.1177/117693510700500005","title":"Perturbation of Interaction Networks for Application to Cancer Therapy","year":2007,"lang":"en","type":"article","venue":"Cancer Informatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Interaction network; Biological network; Computational biology; Computer science; Cancer; Protein–protein interaction; Drug target; Protein Interaction Networks; Prostate cancer; Systems biology; Cancer cell; Drug discovery; Bioinformatics; Biology; Gene; Cancer research; Genetics","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":[0.0009647558,0.0008075517,0.0008545646,0.001208511,0.0004125322,0.0007217199,0.0007006908,0.0007144565,0.001999803],"category_scores_gemma":[0.006347223,0.0004495969,0.000868657,0.001119064,0.0005640704,0.001041609,0.0008550183,0.001092037,0.0003420264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071436,"about_ca_system_score_gemma":0.0008005618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002672322,"about_ca_topic_score_gemma":0.002182113,"domain_scores_codex":[0.9994227,0.0003305716,0.00001923818,0.00007599914,0.0001317667,0.00001987546],"domain_scores_gemma":[0.9974486,0.002008584,0.0001769888,0.0001840722,0.0001336648,0.00004810786],"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":[0.00002718733,0.00001917572,0.0004697878,0.00003896165,0.00003900247,0.00003204477,0.00001598183,0.9785848,0.001309454,0.008205138,0.0004648869,0.01079369],"study_design_scores_gemma":[0.000004388891,0.00000745701,0.0001034813,0.000003752847,0.000005979357,0.00001177886,0.000003698214,0.9813463,0.0004521443,0.0171676,0.0008894512,0.000003966561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02821153,0.0006540118,0.964708,0.00096446,0.00007451742,0.0001133057,0.0005976427,0.001243105,0.003433428],"genre_scores_gemma":[0.513494,0.001408089,0.4804497,0.0003203747,0.0001071521,0.0006435171,0.001196914,0.0002855034,0.002094695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002672322,"threshold_uncertainty_score":0.007773876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336000474826323,"score_gpt":0.3034665275344232,"score_spread":0.29010652278616,"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."}}