{"id":"W4323322991","doi":"10.48550/arxiv.2303.01667","title":"Generalizing Lloyd's algorithm for graph clustering","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Nuclear Security Administration; U.S. Department of Energy","keywords":"Cluster analysis; Computer science; Theoretical computer science; Graph; Sparse matrix; Algorithm; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002419725,0.001310331,0.001800537,0.002958165,0.001482813,0.002088878,0.00355992,0.002670385,0.003886263],"category_scores_gemma":[0.007385047,0.000930355,0.001592068,0.003311703,0.001595033,0.002796461,0.00283333,0.002325115,0.002640571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002379778,"about_ca_system_score_gemma":0.003079656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01885683,"about_ca_topic_score_gemma":0.02014496,"domain_scores_codex":[0.9985124,0.0003688342,0.00009157544,0.000453531,0.0004502367,0.0001234448],"domain_scores_gemma":[0.9983132,0.0005749509,0.0001078202,0.00042663,0.0004927967,0.00008463834],"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":[0.00008373248,0.00008838955,0.0006432547,0.000176441,0.00009182395,0.00008914492,0.0002806244,0.6204907,0.002955337,0.1366486,0.009952297,0.2284997],"study_design_scores_gemma":[0.0000280486,0.00001866254,0.00009216624,0.00001492857,0.000007842622,0.00003682838,0.00003115169,0.93082,0.0007237527,0.0595588,0.008654865,0.00001288979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00128303,0.0001024246,0.9969409,0.0001286503,0.00003646819,0.0000597227,0.00004123011,0.0003514312,0.001056113],"genre_scores_gemma":[0.03371477,0.0002416782,0.9609392,0.0002000785,0.00007184249,0.0002174234,0.0003345126,0.0003460296,0.003934508],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01885683,"threshold_uncertainty_score":0.03749412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1079709854626353,"score_gpt":0.2244235115822793,"score_spread":0.116452526119644,"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."}}