{"id":"W1590594399","doi":"10.1002/0470857005.ch2","title":"Optimal On‐Line Calibration of Testlets","year":2005,"lang":"en","type":"other","venue":"","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Queen's University","funders":"","keywords":"Null (SQL); Line (geometry); Projection (relational algebra); Constraint (computer-aided design); Calibration; Matrix (chemical analysis); Mathematics; Space (punctuation); Algorithm; Combinatorics; Computer science; Applied mathematics; Geometry; Statistics; Data mining; Chemistry; Chromatography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002753219,0.0001132723,0.0001504476,0.0001409832,0.000002908373,0.000001210738,0.00005429955,0.0001676729,0.002564276],"category_scores_gemma":[0.00000594015,0.0001001403,0.00002751938,0.00003823486,0.00001472087,0.00001556565,0.000004569918,0.00008530057,0.00001325705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001333611,"about_ca_system_score_gemma":0.000004066843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002519818,"about_ca_topic_score_gemma":0.00001315984,"domain_scores_codex":[0.9996681,0.000003439865,0.00009821155,0.00007447661,0.00007360073,0.00008220707],"domain_scores_gemma":[0.9998158,0.000006678471,0.00002755021,0.0001259249,0.000006548164,0.000017482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005663679,0.00003353745,0.00001999002,0.00006885613,0.00006059814,0.000001436631,0.000005450712,0.0121555,0.006031056,0.001209119,0.9675556,0.01285313],"study_design_scores_gemma":[0.0001696452,0.0001089545,0.000005048234,0.00007828636,0.00001776766,6.030095e-7,0.000001255073,0.003951427,0.0692103,0.0000238392,0.9262496,0.0001832297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001150147,0.0003456693,0.1886918,0.00001295372,0.00008352738,0.0001019477,0.000007476693,0.0009269812,0.8098181],"genre_scores_gemma":[0.005664729,0.0003954918,0.1225948,0.00008363763,0.0004723574,0.00002382295,0.00004558447,0.0004134149,0.8703061],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06609694,"threshold_uncertainty_score":0.9983475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02138241744717318,"score_gpt":0.2582386502189108,"score_spread":0.2368562327717376,"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."}}