{"id":"W1746594260","doi":"10.1109/icdar.1997.620656","title":"A knowledge-based image understanding environment for document processing","year":2002,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Image processing; Knowledge-based systems; Reuse; Knowledge engineering; Artificial intelligence; Knowledge acquisition; Inference; Context (archaeology); Cognitive neuroscience of visual object recognition; Problem statement; Inference engine; Image (mathematics); Object (grammar); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002048123,0.001061548,0.00117634,0.002260695,0.001415125,0.004784704,0.00392929,0.002148342,0.02958184],"category_scores_gemma":[0.004559077,0.001073573,0.001336876,0.00227194,0.001247164,0.00639431,0.004223366,0.002556617,0.01526268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033914,"about_ca_system_score_gemma":0.001546367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002977056,"about_ca_topic_score_gemma":0.004655945,"domain_scores_codex":[0.998541,0.0002341051,0.0001540667,0.0003858613,0.0005953521,0.00008971543],"domain_scores_gemma":[0.998327,0.0007009535,0.0001028863,0.000453383,0.000285572,0.0001300924],"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":[0.000568276,0.0004803434,0.0007098822,0.0009218086,0.0001663855,0.001100268,0.001355965,0.02037205,0.02236632,0.1445338,0.1054716,0.7019533],"study_design_scores_gemma":[0.0002012244,0.0001355026,0.0007791861,0.000304007,0.0001006745,0.001019929,0.0002185982,0.2364295,0.02611385,0.1784464,0.5560805,0.000170604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001099053,0.0003240774,0.951721,0.0001864847,0.00002648013,0.0001729901,0.001101024,0.03696379,0.008405005],"genre_scores_gemma":[0.01970738,0.0005799602,0.9634043,0.0002481726,0.00004544016,0.0004813494,0.004321684,0.002383038,0.008828662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02958184,"threshold_uncertainty_score":0.09896111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07431386826400342,"score_gpt":0.282189523563462,"score_spread":0.2078756552994586,"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."}}