{"id":"W2036451905","doi":"10.1016/j.camwa.2010.11.029","title":"Detecting critical regions in multidimensional data sets","year":2010,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; Bishop's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Social connectedness; Mathematics; Multidimensional data; Data mining; Theoretical computer science; Pattern recognition (psychology); Artificial intelligence; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0003638948,0.0001441228,0.0002137273,0.0002488694,0.0002031243,0.0001229974,0.001927913,0.00006785529,0.00001463385],"category_scores_gemma":[0.0002382572,0.0001102257,0.00003305052,0.001519847,0.0001527868,0.000361182,0.001007568,0.0003375339,0.00008086806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001281292,"about_ca_system_score_gemma":0.00004970948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001984436,"about_ca_topic_score_gemma":0.0000887918,"domain_scores_codex":[0.998532,0.00002349435,0.0003144349,0.0005810637,0.000268593,0.0002804321],"domain_scores_gemma":[0.9964327,0.001148631,0.00009276181,0.00207897,0.00009397073,0.0001530298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001289883,0.0005897416,0.0003204922,0.00002898148,0.00002509058,0.00001592691,0.000208417,0.0001491734,0.0002594292,0.9564903,0.0007228642,0.04118831],"study_design_scores_gemma":[0.0003613631,0.00004270345,0.001810396,0.00003826198,0.00003669709,0.0001716797,0.00007576808,0.9041036,0.00009018259,0.08080519,0.01208139,0.0003827151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004208005,0.00002157682,0.9925919,0.00235473,0.00006321219,0.000233501,0.00002198809,0.0001492237,0.0003558215],"genre_scores_gemma":[0.2337231,0.000003405054,0.7659649,0.0001486827,0.00003421229,0.00006854352,0.00003654969,0.000006436546,0.00001424117],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9039545,"threshold_uncertainty_score":0.4494875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03972597556941519,"score_gpt":0.3101590476182555,"score_spread":0.2704330720488403,"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."}}