{"id":"W1992504041","doi":"10.1080/00085030.2009.10757606","title":"Forgery by Scanning","year":2009,"lang":"en","type":"article","venue":"Canadian Society of Forensic Science Journal","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Authentication (law); Signature (topology); Computer security; Computer science; Internet privacy; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004229938,0.001067706,0.0007803147,0.002083371,0.002306978,0.003530883,0.001207614,0.002975729,0.01196155],"category_scores_gemma":[0.02046054,0.0006342113,0.0007157251,0.001488903,0.004841872,0.007727157,0.003503753,0.001904864,0.009065766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006223574,"about_ca_system_score_gemma":0.0008505519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006932565,"about_ca_topic_score_gemma":0.0007586813,"domain_scores_codex":[0.9947588,0.001359151,0.0003570224,0.00102771,0.002177398,0.0003198339],"domain_scores_gemma":[0.9855341,0.004144904,0.001191713,0.007673114,0.001268325,0.0001877875],"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":[0.0004843666,0.0001246712,0.01230896,0.0008998508,0.0001879413,0.007351285,0.02803049,0.002692275,0.05485353,0.1519345,0.0379432,0.703189],"study_design_scores_gemma":[0.00003669371,0.0003940558,0.008096511,0.001642185,0.0002577923,0.06044699,0.008823472,0.01465548,0.1768512,0.09711371,0.6312919,0.0003901027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3048818,0.009563898,0.4584886,0.01128091,0.0022688,0.0005099642,0.0006250716,0.003402084,0.2089789],"genre_scores_gemma":[0.6880426,0.003924218,0.2093183,0.003455333,0.0004082934,0.0001150782,0.0004232159,0.0007259152,0.093587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01196155,"threshold_uncertainty_score":0.04001534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01363763012010012,"score_gpt":0.2483467033931919,"score_spread":0.2347090732730918,"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."}}