{"id":"W1982508511","doi":"10.1016/j.patcog.2013.04.019","title":"Order statistics-based parametric classification for multi-dimensional distributions","year":2013,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Order statistic; Statistics; Parametric statistics; Nonparametric statistics; Computer science; Pattern recognition (psychology); Artificial intelligence; Mathematics; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.003774965,0.000750736,0.001439464,0.003008744,0.0007826146,0.002743695,0.00166056,0.001037641,0.001905081],"category_scores_gemma":[0.01766352,0.00052753,0.001784238,0.002327631,0.001683389,0.003365808,0.001998035,0.002977275,0.0009682623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001560604,"about_ca_system_score_gemma":0.001821924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003612924,"about_ca_topic_score_gemma":0.003644323,"domain_scores_codex":[0.9973059,0.0008314547,0.0002557272,0.0004020685,0.0009638635,0.000241041],"domain_scores_gemma":[0.9886745,0.006719181,0.0007369122,0.002153494,0.001455837,0.0002602178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004265704,0.0001801146,0.006103825,0.0002058972,0.0001272558,0.0001775487,0.0004049442,0.2580098,0.008486846,0.1867802,0.005046437,0.5340506],"study_design_scores_gemma":[0.000007064193,0.00003719745,0.0008444047,0.00001540218,0.00001627147,0.00007980992,0.00002971468,0.9247667,0.001488804,0.07169785,0.0009946692,0.00002203651],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01037814,0.0002097469,0.9883002,0.0000938927,0.00002555065,0.00002347622,0.00008647722,0.0003557434,0.0005267541],"genre_scores_gemma":[0.5490577,0.0009817122,0.4429696,0.0001794408,0.0002477872,0.0002559241,0.001556866,0.0004357231,0.004315138],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003774965,"threshold_uncertainty_score":0.01996422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08668302126302689,"score_gpt":0.3163870907231385,"score_spread":0.2297040694601116,"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."}}