{"id":"W2001363923","doi":"10.1520/jfs2004206","title":"A Comparative Reliability Analysis of Computer-Generated Bitemark Overlays","year":2005,"lang":"en","type":"article","venue":"Journal of Forensic Sciences","topic":"Dental Research and COVID-19","field":"Dentistry","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute for Health and Care Research","keywords":"Overlay; Reliability (semiconductor); Adobe photoshop; Medicine; Adobe; Dentistry; Orthodontics; Statistics; Software; Computer science; Mathematics; Multimedia","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02151285,0.0004758003,0.0004009828,0.002708316,0.0003180362,0.0006016369,0.0006667175,0.0004651882,0.001117555],"category_scores_gemma":[0.08563786,0.0004191038,0.0006338481,0.001160081,0.0007624552,0.0006848443,0.0009094952,0.0003404793,0.0004220003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377908,"about_ca_system_score_gemma":0.0003668261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000726971,"about_ca_topic_score_gemma":0.001253719,"domain_scores_codex":[0.9793991,0.009234445,0.001720216,0.001415312,0.007916041,0.0003149035],"domain_scores_gemma":[0.8840646,0.07457632,0.005466154,0.007661243,0.02768217,0.000549492],"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":[0.009992591,0.0005077893,0.2910128,0.002350769,0.001782952,0.0007266608,0.01526191,0.005697241,0.1349568,0.001655427,0.001938336,0.5341167],"study_design_scores_gemma":[0.0003344193,0.007837374,0.8572152,0.000527048,0.001505611,0.003083268,0.00313452,0.03774831,0.07782101,0.001222775,0.009238502,0.0003318466],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413579,0.001811239,0.0525629,0.000064046,0.0001573519,0.0003094138,0.000236575,0.0003924706,0.003108036],"genre_scores_gemma":[0.9709768,0.0003606738,0.02776252,0.00001276373,0.00005072658,0.0001485344,0.0001869084,0.00007853308,0.0004225813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02151285,"threshold_uncertainty_score":0.1137722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05875792174275339,"score_gpt":0.3813011757231497,"score_spread":0.3225432539803963,"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."}}