{"id":"W1858246752","doi":"10.5430/air.v4n2p126","title":"K Nearest Gaussian-A model fusion based framework for imbalanced classification with noisy dataset","year":2015,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noise (video); Computer science; Artificial intelligence; Pattern recognition (psychology); Gaussian noise; Benchmark (surveying); Gaussian; Data mining; Noisy data; Machine learning; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003262309,0.0002284079,0.0002363847,0.0004195936,0.0004387909,0.0006255674,0.002356335,0.0002122879,0.00001500471],"category_scores_gemma":[0.001511262,0.0001960353,0.00004658152,0.001629426,0.0003968753,0.000939557,0.0003231748,0.0005879561,0.0002723993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002673113,"about_ca_system_score_gemma":0.0009170518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007119286,"about_ca_topic_score_gemma":0.00005547691,"domain_scores_codex":[0.9960594,0.0002706265,0.0005191281,0.001001558,0.00131963,0.0008296258],"domain_scores_gemma":[0.9952745,0.0007777131,0.0001661516,0.002174146,0.001228343,0.0003790885],"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":[0.0002808086,0.0003017997,0.0001077933,0.00003127215,0.000008070843,0.000006262881,0.000371097,0.003416237,0.009387814,0.9079275,0.01296664,0.06519469],"study_design_scores_gemma":[0.00004890443,0.0002896176,0.00004429349,0.00005321839,0.000002679615,0.000001921009,0.0002321062,0.7222465,0.0718639,0.2017499,0.003261464,0.000205449],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005578236,0.00002425385,0.9905378,0.006668771,0.0001099916,0.001085396,0.0003530075,0.0003264938,0.0003364131],"genre_scores_gemma":[0.5118448,0.00001508756,0.4865751,0.0002156887,0.00009969786,0.0004908766,0.0006880452,0.00002620904,0.00004453773],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7188303,"threshold_uncertainty_score":0.7994087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4051996626847235,"score_gpt":0.47102421377542,"score_spread":0.06582455109069646,"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."}}