{"id":"W2165668746","doi":"10.1109/icsmc.1995.538133","title":"Automatic processing of information on cheques","year":2002,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cheque; Computer science; Process (computing); Function (biology); Artificial intelligence; Computer security; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006556204,0.0005037409,0.0007993033,0.004794541,0.0007494782,0.001412741,0.0007265128,0.0009182999,0.003334949],"category_scores_gemma":[0.003451801,0.0002551416,0.000397766,0.002714233,0.0004441814,0.001677715,0.0006699268,0.000725763,0.002459896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003030268,"about_ca_system_score_gemma":0.0004402142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199399,"about_ca_topic_score_gemma":0.002555415,"domain_scores_codex":[0.9993466,0.00009076722,0.00004711704,0.0001119971,0.0002944023,0.0001090985],"domain_scores_gemma":[0.9971719,0.0006674502,0.0003385139,0.000369826,0.001363658,0.00008852247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008063256,0.0002026136,0.008354736,0.0004556272,0.00005881318,0.0008781281,0.0005897964,0.002290669,0.1513958,0.003148712,0.01832376,0.813495],"study_design_scores_gemma":[0.0001196026,0.001129238,0.1927593,0.0003915122,0.0002527843,0.006925354,0.002925871,0.2049875,0.398536,0.01521417,0.1763761,0.0003825932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6094678,0.005151649,0.3310469,0.001267813,0.0006878517,0.0006850975,0.00428982,0.01027736,0.03712576],"genre_scores_gemma":[0.6842583,0.002251467,0.2886535,0.0003568024,0.000543818,0.0002056296,0.008339708,0.0004943663,0.01489644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004794541,"threshold_uncertainty_score":0.0111565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221372805706446,"score_gpt":0.2404195775709246,"score_spread":0.21828229700028,"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."}}