{"id":"W4366003831","doi":"10.1007/s41060-023-00389-6","title":"Statistical power, accuracy, reproducibility and robustness of a graph clusterability test","year":2023,"lang":"en","type":"article","venue":"International Journal of Data Science and Analytics","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Toronto","funders":"University of Toronto","keywords":"Statistical hypothesis testing; Statistic; Mathematics; Graph; Test statistic; Cluster analysis; Robustness (evolution); Computer science; Combinatorics; Statistics; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1443976,0.000966095,0.001934552,0.003878181,0.001768812,0.005047827,0.004018805,0.003424897,0.003643607],"category_scores_gemma":[0.6252452,0.0005699889,0.002743644,0.004842645,0.01150578,0.005577407,0.003669973,0.003416045,0.0009222825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508974,"about_ca_system_score_gemma":0.001959721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002428296,"about_ca_topic_score_gemma":0.0009719807,"domain_scores_codex":[0.8415381,0.1017754,0.008258536,0.021346,0.02520947,0.001872402],"domain_scores_gemma":[0.1715778,0.7157265,0.02633893,0.06626151,0.01795259,0.002142683],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005129197,0.0008751113,0.5565547,0.001805349,0.008931457,0.001252775,0.004296195,0.1264836,0.007309719,0.1057141,0.01215434,0.1694933],"study_design_scores_gemma":[0.0009877972,0.004148133,0.1935553,0.000645295,0.002396026,0.002307225,0.002347608,0.5103003,0.01970964,0.2487344,0.01436487,0.0005033789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4433205,0.001910595,0.5341942,0.00346822,0.0009922105,0.0009979084,0.002458262,0.001400318,0.0112578],"genre_scores_gemma":[0.968546,0.00008627727,0.02928696,0.0003085612,0.0002022461,0.0003476251,0.0006166094,0.0001934585,0.0004121687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8556024,"threshold_uncertainty_score":0.7636568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05412285085499116,"score_gpt":0.381376137580153,"score_spread":0.3272532867251619,"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."}}