{"id":"W4407675468","doi":"10.1002/wfs2.70002","title":"From Traces to Intelligence: Forensic Science Contributions to Counterfeiting Understanding Through Profiling of Counterfeit Goods","year":2025,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Forensic Science","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Profiling (computer programming); Counterfeit; Forensic science; Data science; Computer science; Political science; History; Law; Archaeology","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":[0.002209115,0.0002495719,0.0003943369,0.0003680973,0.0008889543,0.0002153475,0.001325161,0.00007618165,0.00002234945],"category_scores_gemma":[0.001157346,0.0002240148,0.000142669,0.002619466,0.001829086,0.00008539186,0.001133926,0.0001358495,0.00005469118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003188224,"about_ca_system_score_gemma":0.0004586058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002157085,"about_ca_topic_score_gemma":0.00005698857,"domain_scores_codex":[0.9969374,0.00006536422,0.0009532686,0.001044857,0.0004875323,0.0005115938],"domain_scores_gemma":[0.9976811,0.00005908946,0.0003259876,0.0009840396,0.0007723331,0.0001774678],"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":[0.00007555538,0.00007527447,0.0003473913,0.00007659991,0.00002359209,5.521285e-7,0.002258301,0.000196852,0.9629042,0.02177246,0.003897104,0.008372142],"study_design_scores_gemma":[0.0001377865,0.0002481688,0.0003016655,0.001349288,0.00004048484,0.000006901766,0.004773271,0.000829368,0.9803708,0.004343031,0.007294835,0.0003044336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.472551,0.002569092,0.5128299,0.00282772,0.002513747,0.001787107,0.0002532718,0.00004264673,0.004625483],"genre_scores_gemma":[0.9891866,0.0002632966,0.00955361,0.0005035996,0.0001310027,0.0001134239,0.00005512018,0.00001204835,0.0001813142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5166356,"threshold_uncertainty_score":0.9135058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0588740233130313,"score_gpt":0.4040506433970146,"score_spread":0.3451766200839833,"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."}}