{"id":"W4389514625","doi":"10.1093/fsr/owad040","title":"Ground penetrating radar used to detect drowning victims under ice","year":2023,"lang":"en","type":"article","venue":"Forensic Sciences Research","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ground-penetrating radar; Remote sensing; Radar; Geology; Snow; Meteorology; Computer science; Geomorphology; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001779913,0.00008897592,0.000107226,0.000292542,0.0005975801,0.0002062263,0.000412,0.0000378755,0.000033541],"category_scores_gemma":[0.0002361201,0.00007773572,0.00003578647,0.004265664,0.0002389982,0.0001313981,0.0001384763,0.0002524531,0.0006044509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005249887,"about_ca_system_score_gemma":0.00004419959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001473554,"about_ca_topic_score_gemma":0.0001115187,"domain_scores_codex":[0.9980655,0.00007536291,0.0001400041,0.0003036958,0.0007540212,0.0006614404],"domain_scores_gemma":[0.9985261,0.001003429,0.000009266962,0.0002254072,0.00007706384,0.0001587492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000492921,0.00001573738,0.0004466362,0.00008293651,0.00002494414,0.000007713317,0.002080633,0.035922,0.7775443,0.036142,0.00438845,0.1433398],"study_design_scores_gemma":[0.0006788828,0.00106797,0.3305865,0.0003156551,0.00001654464,0.00001489655,0.01322852,0.2225092,0.07557405,0.3426898,0.01192871,0.001389285],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852664,0.00002451972,0.006538731,0.0004798467,0.0001516511,0.0002399711,0.000002827191,0.0002871676,0.007008859],"genre_scores_gemma":[0.9660969,0.000004749882,0.03335926,0.0000233293,0.0001537723,0.0000792128,0.000002061739,0.00001689932,0.0002637848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7019702,"threshold_uncertainty_score":0.7769195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.192573655108686,"score_gpt":0.4276955188668914,"score_spread":0.2351218637582054,"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."}}