{"id":"W78882529","doi":"10.55016/ojs/ajer.v55i4.55343","title":"Robustness of Lord’s Formulas for Item Difficulty and Discrimination Conversions Between Classical and Item Response Theory Models","year":2010,"lang":"en","type":"article","venue":"Alberta Journal of Educational Research","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Robustness (evolution); Item response theory; Statistics; Psychology; Range (aeronautics); Econometrics; Computer science; Mathematics; Psychometrics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01753926,0.00009139715,0.000301259,0.0009177646,0.0002890542,0.0001264111,0.0005089642,0.0001070328,0.0003090475],"category_scores_gemma":[0.5444324,0.00005940528,0.00008857797,0.0007739673,0.0004402221,0.0004913314,0.0001502149,0.0004478019,0.000001403011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000325109,"about_ca_system_score_gemma":0.0004425931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002273601,"about_ca_topic_score_gemma":0.00004338531,"domain_scores_codex":[0.9966717,0.0009979557,0.0007061776,0.000247378,0.00112815,0.0002486286],"domain_scores_gemma":[0.5221022,0.4757633,0.0003080786,0.0001708651,0.001470265,0.0001853502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006459028,0.0009383971,0.4617803,0.0001712184,0.0002467993,0.000001115771,0.006995497,0.0007411487,0.01565275,0.3691991,0.02997805,0.1078366],"study_design_scores_gemma":[0.00115091,0.0005938016,0.8189408,0.00009814307,0.00004594782,0.00008033025,0.005141525,0.0182872,0.0004521246,0.1524401,0.002614702,0.0001544884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982236,0.0001553496,0.005682308,0.01051229,0.0003222602,0.0001774201,0.00001453865,4.424326e-7,0.0008994411],"genre_scores_gemma":[0.9880298,0.0000333053,0.007209057,0.00001375474,0.0002577887,0.000007451124,0.000002935257,0.000007613821,0.004438327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5268931,"threshold_uncertainty_score":0.6078793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5762851965354135,"score_gpt":0.549076653154242,"score_spread":0.02720854338117151,"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."}}