{"id":"W3202804502","doi":"10.1016/j.forsciint.2021.111045","title":"Determining the accuracy and errors of estimating a shooter’s position based on cartridge case ejection patterns","year":2021,"lang":"en","type":"article","venue":"Forensic Science International","topic":"Traffic and Road Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cartridge; Position (finance); Sample (material); Set (abstract data type); Computer science; Statistics; Artificial intelligence; Mathematics; Engineering; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001636113,0.00006434773,0.00005579708,0.00008349092,0.0001255885,0.00004592035,0.00008583566,0.00001959193,0.00001892596],"category_scores_gemma":[0.0001373041,0.00004972341,0.00002652497,0.0001495113,0.0001037146,0.0001780154,0.00002889382,0.00007936419,0.000001328109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006638234,"about_ca_system_score_gemma":0.00003979759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001668934,"about_ca_topic_score_gemma":0.00004034058,"domain_scores_codex":[0.9993692,0.000009636312,0.000135153,0.0001323651,0.0002514786,0.0001021884],"domain_scores_gemma":[0.9995962,0.0001248806,0.00003709494,0.0000967616,0.0001159832,0.00002902051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002665486,0.00007118351,0.06047433,0.00005597457,0.00003247909,0.0003418682,0.002104903,0.7370709,0.004686068,0.0009743713,0.0002611017,0.1939002],"study_design_scores_gemma":[0.0001814023,0.0000253089,0.0754898,0.00006534108,0.000005702924,0.0002769445,0.0001705854,0.9173922,0.006291136,0.0000224172,0.00002168712,0.00005746604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757327,0.000004814111,0.0222514,0.0002089405,0.001017508,0.00004793808,0.00002243615,0.00003875028,0.0006755346],"genre_scores_gemma":[0.9965321,0.000001374843,0.003295867,0.00006924992,0.00007575397,0.000003861215,0.00001108442,0.00000538018,0.000005347902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1938427,"threshold_uncertainty_score":0.2027662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419227301921045,"score_gpt":0.262794306253093,"score_spread":0.2486020332338826,"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."}}