{"id":"W2765215346","doi":"10.1111/1556-4029.13678","title":"Measuring the Frequency Occurrence of Handwritten Numeral Characteristics","year":2017,"lang":"en","type":"article","venue":"Journal of Forensic Sciences","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Numeral system; Handwriting; Population; Statistics; Confidence interval; Pattern recognition (psychology); Speech recognition; Mathematics; Computer science; Demography; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001691478,0.000247235,0.0002091888,0.001750979,0.0003675316,0.0006441109,0.0003581932,0.0003411156,0.001637242],"category_scores_gemma":[0.00963479,0.0001762952,0.0001739336,0.0008681096,0.0002457855,0.000668337,0.0006519647,0.000253245,0.0005304976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001715431,"about_ca_system_score_gemma":0.0002635525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229368,"about_ca_topic_score_gemma":0.002921424,"domain_scores_codex":[0.9983764,0.0004533294,0.0002862881,0.0003139498,0.0004884454,0.0000816352],"domain_scores_gemma":[0.9923171,0.001499256,0.003533174,0.0006884196,0.001743251,0.000218755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005344409,0.00006523673,0.9807243,0.00003535459,0.00003067588,0.00006740347,0.0008080634,0.00005780498,0.001892983,0.00006689806,0.000153875,0.01604387],"study_design_scores_gemma":[0.000002415236,0.0001899468,0.9941449,0.00001615783,0.00001782739,0.0007227385,0.001081015,0.0003506413,0.002640238,0.00006460267,0.0007606907,0.000008866657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965096,0.00006645227,0.001667502,0.00001764397,0.000006787892,0.00007320899,0.0002582324,0.00001227526,0.001388243],"genre_scores_gemma":[0.9942584,0.0001209624,0.003983281,0.00002964342,0.00001050047,0.00009525791,0.0003967935,0.000006229309,0.00109882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001750979,"threshold_uncertainty_score":0.008945465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05648224431941549,"score_gpt":0.2946439148672054,"score_spread":0.2381616705477899,"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."}}