{"id":"W1963917975","doi":"10.3758/brm.38.2.344","title":"An SPSS implementation of the nonrecursive outlier deletion procedure with shiftingz score criterion (Van Selst &amp; Jolicoeur, 1994)","year":2006,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Outlier; Computer science; Univariate; Popularity; Simple (philosophy); Data mining; Database; Restructuring; Artificial intelligence; Machine learning; Psychology","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":[0.005586928,0.0002331052,0.0002812778,0.0002982117,0.0004363256,0.0002738058,0.001279991,0.0001357614,0.00004169697],"category_scores_gemma":[0.00008913627,0.0001593578,0.0001035112,0.001333249,0.0002509446,0.0006333599,0.0002984266,0.0005708449,0.00000327686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198022,"about_ca_system_score_gemma":0.0003390465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001111537,"about_ca_topic_score_gemma":0.0006477293,"domain_scores_codex":[0.9934628,0.003654263,0.0004401857,0.0007051111,0.001073017,0.0006645946],"domain_scores_gemma":[0.9976627,0.0002185737,0.0002179439,0.001158587,0.0005861908,0.0001559721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006022935,0.0005037858,0.0275219,0.00009622674,0.00001523421,0.00001361433,0.003981513,0.00001972526,0.230771,0.02505247,0.0006393085,0.7113249],"study_design_scores_gemma":[0.001992997,0.001515529,0.5177717,0.0003004835,0.0001202291,0.0001781064,0.0009004364,0.002044765,0.4287241,0.03848581,0.006956401,0.001009521],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3113284,0.00005266587,0.6870266,0.0003383319,0.00009843652,0.0008938842,0.00001056221,0.0000497457,0.0002013022],"genre_scores_gemma":[0.3019562,0.000005588505,0.6974335,0.00004501155,0.0001066644,0.0002094985,0.00001525941,0.00002848649,0.0001997066],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7103154,"threshold_uncertainty_score":0.6498421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1195939990664034,"score_gpt":0.5160720460885306,"score_spread":0.3964780470221272,"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."}}