{"id":"W4407862351","doi":"10.61186/ijbc.16.4.9","title":"Hematology and Hematopathology Insights Powered by Machine Learning: Shaping the Future of Blood Disorder Management","year":2024,"lang":"en","type":"article","venue":"Iranian Journal of Blood and Cancer","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Hematopathology; Hematology; Engineering ethics; Biology; Medicine; Immunology; Engineering; Biochemistry","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":[0.005379967,0.0004852053,0.001050686,0.002251265,0.0005672778,0.004748941,0.00153326,0.002202691,0.004709675],"category_scores_gemma":[0.01912172,0.0002734108,0.0007024254,0.001006517,0.002074866,0.005349243,0.002426794,0.005635983,0.001104471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00170861,"about_ca_system_score_gemma":0.004089039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001780123,"about_ca_topic_score_gemma":0.003716158,"domain_scores_codex":[0.9984161,0.0006996792,0.0001128212,0.0001978895,0.0004554604,0.000118086],"domain_scores_gemma":[0.9835285,0.01097341,0.0008862533,0.0005243306,0.002963792,0.001123792],"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":[0.0001775211,0.0003822884,0.02021017,0.001556252,0.0001725133,0.0002755538,0.0004204792,0.003406191,0.001465974,0.05437706,0.05700026,0.8605558],"study_design_scores_gemma":[0.0001287389,0.0004669388,0.02102869,0.006789576,0.0003700775,0.001555173,0.002415895,0.03398941,0.002629429,0.4614096,0.4690157,0.0002007599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02081281,0.5011806,0.05899431,0.3857816,0.006060018,0.0001073793,0.0006710333,0.0006994251,0.02569286],"genre_scores_gemma":[0.3561932,0.4663177,0.07951339,0.06404734,0.02737585,0.0002114493,0.000706835,0.0002180826,0.00541612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005379967,"threshold_uncertainty_score":0.02845228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005652672998782283,"score_gpt":0.227403433829391,"score_spread":0.2217507608306088,"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."}}