{"id":"W7095189467","doi":"","title":"LSAC RESEARCH REPORT SERIES � Detection of Answer Copying via Kullback–Leibler Divergence and K-Index","year":2009,"lang":"en","type":"article","venue":"","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Divergence (linguistics); Agency (philosophy); Copying; Discretion; Common law; Accreditation; Public law","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":[0.007405538,0.0008519101,0.001056677,0.005304287,0.001207144,0.003448997,0.001756349,0.001344312,0.0123602],"category_scores_gemma":[0.04467086,0.0003799696,0.000869145,0.003308272,0.001351203,0.004550186,0.002207014,0.001642082,0.007957025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001603153,"about_ca_system_score_gemma":0.003214641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00747146,"about_ca_topic_score_gemma":0.007049442,"domain_scores_codex":[0.9896697,0.002428523,0.0009291594,0.001480618,0.005009264,0.000482742],"domain_scores_gemma":[0.9677893,0.01146793,0.002725342,0.005979351,0.01119553,0.0008424977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008321434,0.0005665306,0.04289062,0.0004533528,0.0002747247,0.0003604847,0.0004436258,0.02366028,0.0185427,0.03119073,0.0401107,0.8406742],"study_design_scores_gemma":[0.000118087,0.0005186918,0.04510743,0.00008249434,0.00006460603,0.001350521,0.0004479604,0.8468761,0.04202802,0.03919878,0.02397556,0.0002317674],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2048019,0.002506877,0.7507199,0.001651023,0.000747891,0.0007234375,0.00488621,0.006877498,0.0270853],"genre_scores_gemma":[0.5708333,0.0009610325,0.3900838,0.0001917366,0.000383439,0.0004500939,0.01426417,0.0006805041,0.02215185],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0123602,"threshold_uncertainty_score":0.04134893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04406817888694091,"score_gpt":0.3470701085444997,"score_spread":0.3030019296575587,"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."}}