{"id":"W202209444","doi":"10.1007/978-3-319-03410-2_3","title":"Clustering Items in Time-Stamped Databases Induced by Stability","year":2013,"lang":"en","type":"book-chapter","venue":"Intelligent systems reference library","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Partition (number theory); Variation (astronomy); Cluster analysis; Stability (learning theory); Computer science; Cluster (spacecraft); Degree (music); Database; Data mining; Class (philosophy); Mathematics; Artificial intelligence; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001890386,0.0004877123,0.001449414,0.005556798,0.0008269417,0.003187311,0.002504387,0.0009302066,0.001590799],"category_scores_gemma":[0.01631,0.0005914696,0.001010378,0.01092122,0.0009407793,0.003423856,0.001874163,0.001019364,0.0007704132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050541,"about_ca_system_score_gemma":0.0008982054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001946873,"about_ca_topic_score_gemma":0.002110335,"domain_scores_codex":[0.9969908,0.0003554471,0.0004065458,0.0007441874,0.001315265,0.0001876516],"domain_scores_gemma":[0.990362,0.004315415,0.001242002,0.001436664,0.002298589,0.0003452854],"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":[0.002375012,0.0003056002,0.04492767,0.001068245,0.0005675685,0.001150737,0.00125771,0.2299579,0.03160022,0.08395611,0.01244964,0.5903836],"study_design_scores_gemma":[0.00005092083,0.0002410581,0.007973152,0.00008725467,0.0001355914,0.0006749167,0.0004166396,0.8837916,0.009326641,0.09194339,0.00530214,0.00005662116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2222289,0.002254527,0.7689727,0.0005444796,0.0001991222,0.0001956792,0.002445717,0.0009720469,0.002186914],"genre_scores_gemma":[0.6909378,0.00171416,0.2962365,0.0001643358,0.0003031759,0.0002216993,0.00681542,0.0001671267,0.003439845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005556798,"threshold_uncertainty_score":0.009997487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.084136961069966,"score_gpt":0.2619171409232814,"score_spread":0.1777801798533154,"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."}}