{"id":"W1583644050","doi":"10.1007/3-540-45656-2_3","title":"Resolving Minsky’s Paradox : The d-Dimensional Normal Distribution Case","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Classifier (UML); Pairwise comparison; Covariance; Linear discriminant analysis; Pattern recognition (psychology); Bayes' theorem; Bayes classifier; Artificial intelligence; Linear classifier; Mathematics; Quadratic classifier; Perceptron; Naive Bayes classifier; Computer science; Linearity; Algorithm; Mathematical optimization; Statistics; Bayesian probability; Support vector machine; Artificial neural network; Engineering","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":[0.008058678,0.0005785399,0.002016698,0.001591375,0.002658688,0.005555731,0.00214705,0.00536858,0.004834379],"category_scores_gemma":[0.04833585,0.0006807555,0.0009522744,0.002551435,0.006166046,0.01602261,0.005496743,0.006768892,0.0007726696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001583755,"about_ca_system_score_gemma":0.001343995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550938,"about_ca_topic_score_gemma":0.0009394233,"domain_scores_codex":[0.9964275,0.001629121,0.0001857701,0.0005277523,0.0008635708,0.0003662913],"domain_scores_gemma":[0.9779975,0.01639546,0.001135508,0.00235561,0.00113203,0.0009839064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000309015,0.00001143586,0.0001699408,0.00002102674,0.000009273714,0.00009461128,0.00008397,0.001007249,0.00005252013,0.9907683,0.002953621,0.00479721],"study_design_scores_gemma":[0.000007219605,0.000001470669,0.00002682897,0.000004203065,0.000001256018,0.00005361204,0.00002271788,0.00275242,0.00001859213,0.9964126,0.0006951451,0.00000405831],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2070799,0.0117535,0.4249156,0.1407321,0.0023523,0.00004866061,0.0006621593,0.0003544091,0.2121015],"genre_scores_gemma":[0.9508758,0.003504592,0.02895075,0.005319451,0.001922001,0.00005615171,0.0001258813,0.0001373414,0.009108013],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008058678,"threshold_uncertainty_score":0.04261887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06029501419615856,"score_gpt":0.351773974706829,"score_spread":0.2914789605106704,"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."}}