{"id":"W4386497976","doi":"10.1145/3622940","title":"Discovering Interesting Patterns from Hypergraphs","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Knowledge Discovery from Data","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Hypergraph; Data mining; Computer science; Theoretical computer science; Mathematics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001784589,0.0002676104,0.0002392392,0.0002125737,0.0003794886,0.0007632081,0.005608071,0.00007553591,0.00005317451],"category_scores_gemma":[0.00007505007,0.000259243,0.00009454446,0.0008407405,0.0000527856,0.003305503,0.0006782473,0.0003165875,0.0009672329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004261708,"about_ca_system_score_gemma":0.00007908837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001690724,"about_ca_topic_score_gemma":0.0008285621,"domain_scores_codex":[0.9977459,0.00006013424,0.0003523463,0.001214921,0.0002411923,0.0003854932],"domain_scores_gemma":[0.9936139,0.00078367,0.00008274014,0.00536118,0.00003165882,0.0001268561],"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":[0.00001708128,0.0006436243,0.001733323,0.0000253585,0.0003151542,0.00003847947,0.002225944,0.0004784999,0.00239864,0.001366978,0.006386356,0.9843706],"study_design_scores_gemma":[0.002427894,0.0002290162,0.07162513,0.00137981,0.0003279841,0.000014695,0.002454008,0.8276272,0.01294179,0.02799422,0.0502274,0.002750898],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1279754,0.00008236289,0.8534598,0.0005801893,0.0009639037,0.0001350487,0.01607302,0.0005542049,0.0001760652],"genre_scores_gemma":[0.9473358,0.0002203319,0.04453597,0.000111669,0.0002590898,0.00009260102,0.006855067,0.00004801966,0.0005413988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9816197,"threshold_uncertainty_score":0.999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07976721731493004,"score_gpt":0.3152483108612908,"score_spread":0.2354810935463608,"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."}}