{"id":"W2342671210","doi":"10.1109/tkde.2016.2525993","title":"Clearing Contamination in Large Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Clearing; Graph; Mathematical optimization; Theoretical computer science; Algorithm; Mathematics","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":[0.0001588913,0.0001020901,0.0001231718,0.0001321469,0.00004885432,0.00002107218,0.0001406965,0.00002836794,0.00008448507],"category_scores_gemma":[9.637107e-7,0.00008645706,0.0000264486,0.0001691973,0.00000827747,0.0002396475,0.000007326276,0.0001161645,0.000009892194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002267424,"about_ca_system_score_gemma":0.000006393158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001891113,"about_ca_topic_score_gemma":0.00006231474,"domain_scores_codex":[0.9993988,0.00001374128,0.0001449974,0.000225724,0.00003993278,0.0001767972],"domain_scores_gemma":[0.9995095,0.00009843837,0.00001826215,0.0003179704,0.00001506634,0.00004078149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002289624,0.0003963704,0.008249252,0.00002454974,0.0001449265,0.000002522794,0.0002259465,0.01561077,0.001974875,0.005240167,0.0004813315,0.9676264],"study_design_scores_gemma":[0.0009128187,0.00003297266,0.005754053,0.000244409,0.00004834311,9.559981e-7,0.00003758117,0.9813463,0.002689136,0.0001085323,0.008496715,0.0003281516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01841407,0.00007777177,0.9808279,0.00001668861,0.00009217781,0.00007085958,0.00004020201,0.00007079214,0.0003895967],"genre_scores_gemma":[0.9992604,0.00003534817,0.0004299923,0.000003225075,0.00009645808,0.00001715768,0.00001679687,0.00001453145,0.0001260963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9808463,"threshold_uncertainty_score":0.3525617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455598534556424,"score_gpt":0.2634419975948157,"score_spread":0.2488860122492514,"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."}}