{"id":"W2047034391","doi":"10.1081/sta-200045867","title":"Robust Reduced Rank Mixture Discriminant Analysis","year":2005,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Linear discriminant analysis; Mathematics; Outlier; Rank (graph theory); Optimal discriminant analysis; Pattern recognition (psychology); Covariance; Multiple discriminant analysis; Statistics; Subspace topology; Mixture model; Gaussian; Discriminant; Kernel Fisher discriminant analysis; Covariance matrix; Artificial intelligence; Computer science; Combinatorics; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.006378057,0.0002165892,0.0005655087,0.0002112908,0.00021285,0.00004184099,0.0003385979,0.0001171401,0.0001598028],"category_scores_gemma":[0.005914434,0.000187355,0.00007065383,0.0004281248,0.000303161,0.0001346937,0.0001772957,0.0003867623,0.000002389004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005502265,"about_ca_system_score_gemma":0.00002579838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001374717,"about_ca_topic_score_gemma":0.00008264084,"domain_scores_codex":[0.9936174,0.005010461,0.0006302291,0.0003321614,0.0001345941,0.0002751449],"domain_scores_gemma":[0.9856529,0.01290394,0.0002218383,0.0009798559,0.0001145948,0.0001268404],"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":[0.00008345745,0.00008393308,0.00002394726,0.00004116301,0.00008058904,0.000001204917,0.001087686,0.0002628391,0.0004183312,0.7415333,0.0001368951,0.2562467],"study_design_scores_gemma":[0.0004135103,0.00002476188,0.0008786453,0.00005039598,0.0005228878,0.000003512742,0.0004514501,0.01805591,0.0004811733,0.9765543,0.002321599,0.0002418292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009024396,0.001319633,0.9952638,0.0002315311,0.00004496264,0.0003032745,0.000113368,0.00004514863,0.001775851],"genre_scores_gemma":[0.04526415,0.0007133002,0.9529325,0.0001332638,0.00002639428,0.0001187421,0.0000384747,0.00002656617,0.0007465915],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2560049,"threshold_uncertainty_score":0.7640114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1592118916519817,"score_gpt":0.5010615256169871,"score_spread":0.3418496339650055,"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."}}