{"id":"W2033872871","doi":"10.3102/1076998613481500","title":"A Two-Decision Model for Responses to Likert-Type Items","year":2013,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kronos (Canada)","funders":"","keywords":"Likert scale; Item response theory; Set (abstract data type); Decision model; Econometrics; Functional response; Model selection; Response time; Statistics; Computer science; Mathematics; Machine learning; Psychometrics","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":[0.001934876,0.00009649088,0.0002472943,0.0004270692,0.0001393793,0.0002575074,0.0003133421,0.0000373992,0.0003475581],"category_scores_gemma":[0.04071126,0.00006302931,0.000053574,0.0005408177,0.00004361416,0.0002244372,0.00005324061,0.0001052036,0.00002547736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003261423,"about_ca_system_score_gemma":0.0002488319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000560406,"about_ca_topic_score_gemma":0.000007992173,"domain_scores_codex":[0.9981045,0.00008530316,0.0007773568,0.0001748197,0.0006935392,0.0001645255],"domain_scores_gemma":[0.9742002,0.02290869,0.0004387491,0.0001403594,0.002069937,0.0002420754],"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":[0.000438651,0.0004316139,0.09845335,0.000005633981,0.00001238768,0.00000236154,0.0006875027,0.0011398,0.001945021,0.007118654,0.3012902,0.5884748],"study_design_scores_gemma":[0.0006175372,0.001086615,0.3184436,0.00004082298,0.00004457899,0.0001053425,0.000719419,0.02278476,0.00003125965,0.649464,0.006450237,0.0002118728],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6887818,0.000143496,0.3083389,0.001527975,0.000952607,0.0001394314,0.00007961978,0.000001830438,0.00003435371],"genre_scores_gemma":[0.4096995,0.00001250356,0.5879563,0.0001780831,0.0001755857,0.00000654931,0.00000212361,0.000005373647,0.001963997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6423453,"threshold_uncertainty_score":0.9673693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5866905625763341,"score_gpt":0.5681326453150991,"score_spread":0.01855791726123501,"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."}}