{"id":"W4410747573","doi":"10.1057/s41599-025-04959-w","title":"Two-stage polytomous attribute estimation for cognitive diagnostic models: overcoming computational challenges in large-scale assessments with many polytomous attributes","year":2025,"lang":"en","type":"article","venue":"Humanities and Social Sciences Communications","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Polytomous Rasch model; Cognition; Scale (ratio); Stage (stratigraphy); Estimation; Computer science; Econometrics; Cognitive psychology; Item response theory; Psychology; Mathematics; Psychometrics; Clinical psychology; Psychiatry; Economics; Geography; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01628739,0.0007941131,0.00130558,0.001358738,0.0008391816,0.001552268,0.002304835,0.001363271,0.001953961],"category_scores_gemma":[0.06097193,0.0007730206,0.001146361,0.001415673,0.001322893,0.002144586,0.002506874,0.003399055,0.000334365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239048,"about_ca_system_score_gemma":0.003227604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009910839,"about_ca_topic_score_gemma":0.01369104,"domain_scores_codex":[0.9938889,0.004634527,0.0002201315,0.0006508028,0.0004695637,0.0001360583],"domain_scores_gemma":[0.9395135,0.05411753,0.001624212,0.002803057,0.001369499,0.0005721427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005157599,0.0003410041,0.03148453,0.000328028,0.0003823277,0.0002389638,0.0009104289,0.6168828,0.001744282,0.06945095,0.002410939,0.27531],"study_design_scores_gemma":[0.00002850637,0.00003145306,0.001012321,0.00001690458,0.00001795619,0.00003390653,0.00003385279,0.9756866,0.0002639697,0.02244722,0.0004122026,0.00001512213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02558488,0.0001577639,0.9731609,0.0003374467,0.00001701716,0.0001223939,0.00006952121,0.0002600327,0.0002900803],"genre_scores_gemma":[0.3144975,0.0001602665,0.6838268,0.0002068488,0.00004723778,0.0003886044,0.0002776466,0.00005161509,0.0005434689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01628739,"threshold_uncertainty_score":0.08613694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1856263267904239,"score_gpt":0.3746113545486136,"score_spread":0.1889850277581896,"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."}}