{"id":"W4403142507","doi":"10.1016/b978-0-443-24028-7.00021-0","title":"Medical diagnosis using image processing techniques","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Computer vision; Image processing; Artificial intelligence; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002613673,0.0005788615,0.000529995,0.0003742383,0.0001232181,0.001361616,0.001686038,0.0003064582,0.00006874876],"category_scores_gemma":[0.00006570684,0.0005365938,0.0003591617,0.00005399613,0.0003502187,0.0006111577,0.001387608,0.0005962335,0.0003100414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001415585,"about_ca_system_score_gemma":0.0006666256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.500095e-7,"about_ca_topic_score_gemma":0.000003109327,"domain_scores_codex":[0.9968541,0.00001405405,0.0005463799,0.000982554,0.001145206,0.000457739],"domain_scores_gemma":[0.9982998,0.00006826113,0.0002022462,0.0008782325,0.000164441,0.0003870047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[8.931655e-7,0.0000180331,0.000002808631,0.0003279825,0.00004638992,0.0006985391,0.00005222157,4.571839e-8,0.000008272373,0.02317707,0.0004503287,0.9752174],"study_design_scores_gemma":[0.000063054,0.0000316985,7.777189e-7,0.004547813,0.000141726,0.0001764111,0.000001413879,0.0008489288,0.0007461319,0.1234525,0.8693019,0.0006876487],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000006531632,0.00590514,0.001117681,0.0003258829,0.0003879144,0.0003830057,0.00002981235,0.001438771,0.9904053],"genre_scores_gemma":[0.0003793944,0.0000946115,0.03737958,0.00106496,0.0005784611,0.0001081433,0.00001156976,0.0002006505,0.9601826],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9745297,"threshold_uncertainty_score":0.9997085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01780495839693414,"score_gpt":0.2789887653654498,"score_spread":0.2611838069685157,"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."}}