{"id":"W4408640756","doi":"10.1007/s42979-025-03801-z","title":"DevDynaP: A Dynamic Local Community Detection Algorithm","year":2025,"lang":"en","type":"article","venue":"SN Computer Science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Algorithm","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":[0.0005280187,0.0001092258,0.0001382141,0.0002206474,0.0006787481,0.0001424039,0.0007277185,0.00001819722,0.00002124411],"category_scores_gemma":[0.000001771551,0.0001068083,0.00007210465,0.00145394,0.0004126478,0.0001811326,0.000548695,0.0002747425,0.00001256255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009902096,"about_ca_system_score_gemma":0.0001020596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000589547,"about_ca_topic_score_gemma":0.00008510217,"domain_scores_codex":[0.9990751,0.00008879565,0.000161482,0.0002461231,0.0001723584,0.0002561584],"domain_scores_gemma":[0.9992155,0.00006473537,0.00005116503,0.0004972059,0.0001191145,0.0000523179],"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":[8.535894e-7,0.0000506554,0.0005278671,0.000001709427,0.00001269554,2.655936e-7,0.00005553122,0.0003246068,0.0003613988,0.002110461,0.00008502186,0.996469],"study_design_scores_gemma":[0.00008861712,0.00003415382,0.005467311,0.0000202726,0.00001121451,7.551784e-7,0.00003684697,0.9655815,0.003736247,0.0241788,0.0007319138,0.0001124139],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04852305,0.00001127798,0.9490758,0.00005407153,0.000217639,0.00008679876,0.000001811343,0.0001245106,0.00190501],"genre_scores_gemma":[0.9456568,3.749059e-7,0.05412986,0.00009196447,0.00005079616,0.00001079972,0.000003767051,0.000003446485,0.00005212805],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9963565,"threshold_uncertainty_score":0.522045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005072227009594658,"score_gpt":0.2678965391287106,"score_spread":0.2628243121191159,"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."}}