{"id":"W7098358292","doi":"","title":"LSAC RESEARCH REPORT SERIES � Detection of Advance Item Knowledge Using Response Times in Computer Adaptive Testing","year":2006,"lang":"en","type":"article","venue":"","topic":"Reconstructive Facial Surgery Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Agency (philosophy); Voting; Test (biology); Legal research; Association (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01755495,0.0005815635,0.000586469,0.005253297,0.0009038227,0.00149925,0.001655855,0.0008455132,0.00687102],"category_scores_gemma":[0.07631189,0.0004165829,0.0006398094,0.003347642,0.0006705998,0.001556065,0.0008614997,0.001181949,0.003227906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00285802,"about_ca_system_score_gemma":0.006252282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.132249,"about_ca_topic_score_gemma":0.1477075,"domain_scores_codex":[0.9839103,0.005420791,0.001268374,0.001056965,0.007912518,0.0004311095],"domain_scores_gemma":[0.8729281,0.05497152,0.007320998,0.005810043,0.05660655,0.002362756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001144965,0.002537966,0.5520433,0.0004630056,0.0002093366,0.0001277957,0.001211331,0.002334364,0.003350504,0.0009237097,0.02713005,0.4085237],"study_design_scores_gemma":[0.0001913418,0.001727042,0.9652631,0.0001471252,0.0001355404,0.0002850564,0.0007593713,0.01046099,0.005966439,0.0006146979,0.01437781,0.00007163968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8307175,0.003039665,0.05739819,0.002744418,0.001001379,0.01072934,0.02341384,0.001617953,0.06933774],"genre_scores_gemma":[0.8724171,0.001727584,0.0778531,0.0006121346,0.0003281248,0.006090986,0.01704916,0.0003812799,0.0235406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132249,"threshold_uncertainty_score":0.2629585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08478908850025374,"score_gpt":0.3818942400081398,"score_spread":0.297105151507886,"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."}}