{"id":"W2621092612","doi":"10.1111/1556-4029.13363","title":"Tape Lift Sampling of Chemical Threat Agents","year":2017,"lang":"en","type":"article","venue":"Journal of Forensic Sciences","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shared Health","funders":"","keywords":"Tile; Lift (data mining); Materials science; Cartridge; Forensic engineering; Computer science; Composite material; Environmental science; Engineering","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":[0.0004729395,0.00009194418,0.0002467107,0.00005276993,0.0001327849,0.00004872012,0.0007578532,0.00005131427,0.00007477303],"category_scores_gemma":[0.0004586776,0.00006198417,0.0001623464,0.00008321524,0.0004364487,0.0002523979,0.0001615222,0.0001620729,0.000004457338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002963248,"about_ca_system_score_gemma":0.00002615923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002248413,"about_ca_topic_score_gemma":0.000001249646,"domain_scores_codex":[0.9987998,0.000005147703,0.0003952138,0.0001178094,0.0004836074,0.0001984337],"domain_scores_gemma":[0.9990301,0.00009296599,0.0004970673,0.000194983,0.00008672194,0.000098231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001548121,0.0002336207,0.0120154,0.000174131,0.0002206661,0.00004335092,0.00051601,0.003735149,0.8666583,0.01139179,0.004098904,0.1007578],"study_design_scores_gemma":[0.0009694187,0.0001487133,0.006057453,0.0005094672,0.00009409368,0.00005540781,0.0001931035,0.008099918,0.9705306,0.009542418,0.003539896,0.0002595463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922276,0.0002274673,0.00152928,0.0008573132,0.0004464771,0.00003687886,0.000001709877,0.000008352415,0.004664908],"genre_scores_gemma":[0.9921592,0.00007555235,0.007422774,0.00004072658,0.0002446039,3.085794e-7,2.455238e-7,0.000004746154,0.0000518054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1038722,"threshold_uncertainty_score":0.2527641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06203672768546915,"score_gpt":0.3229689108056031,"score_spread":0.2609321831201339,"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."}}