{"id":"W7097206564","doi":"","title":"Graphs and Networks Lecture 19 Graph Clustering: Spectral Methods and Normalized Cuts","year":2010,"lang":"en","type":"article","venue":"","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Heuristics; Partition (number theory); Graph partition; Spectral clustering; Graph; Segmentation; Cut","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000677332,0.0001769758,0.0001854429,0.000135711,0.0002137638,0.0002368345,0.0003662331,0.0001158729,0.00003007105],"category_scores_gemma":[0.00002105846,0.0001369425,0.00006294171,0.0003934701,0.0001612433,0.0003269136,0.0002536782,0.0003595922,9.326328e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001711648,"about_ca_system_score_gemma":0.00001044905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002241165,"about_ca_topic_score_gemma":0.00006878162,"domain_scores_codex":[0.998904,0.0001299625,0.0001514245,0.0003992473,0.00009127098,0.0003241038],"domain_scores_gemma":[0.9991957,0.0001504175,0.00004473399,0.000363039,0.00002373984,0.0002224028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003074797,0.00004653499,0.002108229,0.00002228554,0.0000615935,0.00003231478,0.001015439,0.0002113013,0.01001318,0.7861627,0.0003827086,0.199913],"study_design_scores_gemma":[0.001044101,0.0001586782,0.008093167,0.000009483947,0.00002227802,0.0005435092,0.00002817724,0.3519367,0.004151294,0.6299796,0.003469296,0.0005637212],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05047467,0.0003160897,0.9460641,0.000342175,0.0006649317,0.000112117,6.077209e-7,0.0002028648,0.001822436],"genre_scores_gemma":[0.4316703,0.00008054747,0.5673413,0.0006804175,0.00005114336,0.000005770424,0.000001024872,0.000008574987,0.0001608773],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3811957,"threshold_uncertainty_score":0.5584352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007981789090917072,"score_gpt":0.2730976319001127,"score_spread":0.2651158428091956,"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."}}