{"id":"W3027736642","doi":"10.22237/jmasm/1571745720","title":"On Statistical Significance of Discriminant Function Coefficients","year":2020,"lang":"en","type":"article","venue":"Journal of Modern Applied Statistical Methods","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Calgary","funders":"","keywords":"Mathematics; Discriminant; Discriminant function analysis; Linear discriminant analysis; Statistics; Multivariate statistics; Statistical hypothesis testing; Optimal discriminant analysis; Statistical significance; Function (biology); Applied mathematics; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00786662,0.0003012639,0.001162424,0.0002265038,0.00009490614,0.0001141592,0.000828848,0.0001317393,0.000909085],"category_scores_gemma":[0.01616781,0.0002084852,0.0001723284,0.0006116178,0.0004427938,0.0001329074,0.0001436496,0.0006158607,0.00006718369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000854277,"about_ca_system_score_gemma":0.0001789194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002276492,"about_ca_topic_score_gemma":1.235e-7,"domain_scores_codex":[0.991891,0.002158766,0.002235677,0.0005972162,0.002726678,0.0003906202],"domain_scores_gemma":[0.980056,0.01728517,0.001160932,0.0003834245,0.0004670697,0.0006474406],"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":[0.003454174,0.0003439436,0.00001795983,0.00002386283,0.00004849631,0.00003285188,0.0005126061,0.002991526,0.2037182,0.2638051,0.002358656,0.5226926],"study_design_scores_gemma":[0.001769094,0.003996132,0.002706037,0.00003561423,0.0001761656,0.00002116406,0.000700857,0.1380923,0.04661629,0.8037129,0.001780046,0.0003934204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001539114,0.0000934887,0.9930725,0.0002520821,0.0004688912,0.0002909338,0.0001648452,0.00001414939,0.004103983],"genre_scores_gemma":[0.4523569,0.000002768234,0.5471748,0.0003520376,0.00006859561,0.000004871981,0.00000180426,0.00002001837,0.00001816794],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5399078,"threshold_uncertainty_score":0.9953843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1965310144243367,"score_gpt":0.4860267648000066,"score_spread":0.2894957503756699,"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."}}