{"id":"W1982733046","doi":"10.1198/016214506000000096","title":"Principal Components Analysis Based on Multivariate MM Estimators With Fast and Robust Bootstrap","year":2006,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Estimator; Principal component analysis; Mathematics; Asymptotic distribution; Robustness (evolution); Multivariate statistics; Consistency (knowledge bases); Eigenvalues and eigenvectors; Inference; M-estimator; Robust statistics; Statistics; Computer science; Artificial intelligence","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":[0.0006765859,0.0001593841,0.000571558,0.0001150436,0.0001242151,0.00004692839,0.0001201565,0.00003416638,0.00001248198],"category_scores_gemma":[0.001767128,0.00009536959,0.0001050729,0.0004044573,0.0001429159,0.00006352791,0.00002320125,0.0002884629,7.480455e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002590529,"about_ca_system_score_gemma":0.00004308588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001027141,"about_ca_topic_score_gemma":0.00002952357,"domain_scores_codex":[0.9979911,0.0003939897,0.0005176798,0.0001603642,0.0007022537,0.0002346208],"domain_scores_gemma":[0.994397,0.003644808,0.001491622,0.0001434141,0.000215434,0.0001076963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002156,0.002086266,0.3396772,0.0001138618,0.002525933,0.0001307415,0.0002475232,0.39797,0.001144794,0.2257055,0.00167731,0.02656484],"study_design_scores_gemma":[0.0009251164,0.000411482,0.6226211,0.00004936026,0.001234873,0.000006097732,0.00003687876,0.31116,0.00004381548,0.06329559,0.00003851326,0.0001772241],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1345585,0.000002010916,0.8646339,0.0003793198,0.00003920767,0.00009432196,0.0001355339,0.000009835499,0.0001474717],"genre_scores_gemma":[0.5332159,7.366198e-7,0.466613,0.00007657279,0.00003440634,0.000001693019,0.000003067377,0.00001086197,0.00004366952],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3986575,"threshold_uncertainty_score":0.3889059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05271612320927879,"score_gpt":0.370291191177527,"score_spread":0.3175750679682482,"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."}}