{"id":"W2138688019","doi":"10.1007/s11336-013-9373-x","title":"Generalized Functional Extended Redundancy Analysis","year":2013,"lang":"en","type":"article","venue":"Psychometrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Universidade de Santiago de Compostela; National Research Foundation of Korea","keywords":"Generalized linear model; Redundancy (engineering); Computer science; Component (thermodynamics); Exponential family; Algorithm; Function (biology); Data mining; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00282814,0.0002339469,0.0005629021,0.003152951,0.0001833012,0.0006199484,0.000848391,0.0001156807,0.05671374],"category_scores_gemma":[0.003604028,0.0001746047,0.0005616044,0.01564379,0.0001285005,0.0006340981,0.0001091999,0.0001665825,0.007418346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007435607,"about_ca_system_score_gemma":0.00003496062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000104101,"about_ca_topic_score_gemma":0.0000032631,"domain_scores_codex":[0.9950542,0.0005669552,0.0008918138,0.0009121192,0.002149427,0.0004254215],"domain_scores_gemma":[0.9959892,0.001740219,0.0002823302,0.001163215,0.0005016482,0.0003234023],"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":[0.000269138,0.0009749392,0.08931499,0.0000039142,0.001562135,0.000008572096,0.0004186741,0.0007468825,0.1085326,0.01261861,0.2957841,0.4897655],"study_design_scores_gemma":[0.001258393,0.0001638292,0.8976009,0.000002873248,0.0001565355,0.000009328528,0.0003411902,0.005709743,0.005747991,0.05207693,0.03642567,0.0005065521],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6090467,0.002314235,0.3099356,0.00149882,0.002751499,0.0007032945,0.00002207174,0.0002294382,0.07349835],"genre_scores_gemma":[0.7862081,0.00002628087,0.1898912,0.0006626668,0.0002049443,0.0001183942,0.00001303428,0.00002236602,0.02285302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.808286,"threshold_uncertainty_score":0.9933545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.194186350982833,"score_gpt":0.452341991218989,"score_spread":0.258155640236156,"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."}}