{"id":"W2166699357","doi":"10.1109/ccece.2013.6567779","title":"Bleeding detection in wireless capsule endoscopy based on color features from histogram probability","year":2013,"lang":"en","type":"article","venue":"","topic":"Gastrointestinal Bleeding Diagnosis and Treatment","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Artificial intelligence; Color histogram; Capsule endoscopy; Grayscale; Histogram; Histogram equalization; Computer vision; RGB color model; Computer science; Color space; Pattern recognition (psychology); RGB color space; Skew; Feature (linguistics); Color image; Image (mathematics); Image processing; Medicine; Radiology","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":[0.0004621602,0.0003536766,0.0003823196,0.00159579,0.0001921423,0.0006590261,0.0003417331,0.0003582819,0.0006200254],"category_scores_gemma":[0.002091819,0.0002072367,0.0003914642,0.000954352,0.0003094336,0.0009189073,0.0003794471,0.000322012,0.0003231825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002719456,"about_ca_system_score_gemma":0.0002081247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001155345,"about_ca_topic_score_gemma":0.0007521871,"domain_scores_codex":[0.9996319,0.00006897843,0.00002150312,0.00005728737,0.0001848702,0.00003550421],"domain_scores_gemma":[0.9992962,0.000342782,0.0001153774,0.00004718557,0.0001680282,0.00003035376],"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":[0.0008290155,0.0001638193,0.03712507,0.0002247471,0.0001373279,0.0005116172,0.0001317409,0.02694369,0.1440814,0.001987081,0.001711309,0.7861533],"study_design_scores_gemma":[0.00005251621,0.0005144134,0.0785115,0.00003351106,0.0002071109,0.002830286,0.0001011424,0.8079677,0.1041842,0.002481221,0.003023332,0.00009300279],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1791397,0.0008051149,0.816895,0.000128638,0.00005239227,0.00007356237,0.0001351799,0.001061919,0.001708503],"genre_scores_gemma":[0.8486283,0.000555372,0.1496163,0.00003451408,0.00006417387,0.00004412099,0.0001708287,0.00004612468,0.0008403115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00159579,"threshold_uncertainty_score":0.002444148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551990988916203,"score_gpt":0.2461959865891027,"score_spread":0.2306760766999407,"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."}}