{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002876014,0.0004499996,0.0004836132,0.0003384046,0.0009699767,0.0006628055,0.002105271,0.0002440068,0.0001368681],"category_scores_gemma":[0.003799486,0.0002886481,0.0001268014,0.0009245325,0.001590866,0.0005573161,0.001117805,0.001132289,0.0001233285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000359329,"about_ca_system_score_gemma":0.0003484898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003678052,"about_ca_topic_score_gemma":0.0001347533,"domain_scores_codex":[0.993762,0.00007787338,0.0009280377,0.001509006,0.002994976,0.0007281769],"domain_scores_gemma":[0.9909633,0.006547928,0.000441425,0.001196032,0.0006315335,0.0002197331],"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":[0.00002361715,0.00001654565,0.00016769,0.000006722382,0.000004962367,0.002701387,0.0002261114,0.1037758,0.00002000548,0.007131988,0.0001678087,0.8857573],"study_design_scores_gemma":[0.0002366617,0.0001016933,0.0003185965,0.0002147969,0.00001566071,0.003077722,0.000002494514,0.319426,0.0002215246,0.6618636,0.01385368,0.0006675464],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000417552,0.000492322,0.993915,0.0008131152,0.00198214,0.0002551231,0.00006220779,0.00005001357,0.002012569],"genre_scores_gemma":[0.8805401,0.0000184585,0.1156029,0.0007367239,0.001560532,0.00001268841,0.00001930922,0.00004467762,0.001464547],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8850898,"threshold_uncertainty_score":0.9999565,"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."}}