{"id":"W4416950181","doi":"10.1016/j.engappai.2025.113401","title":"Automatic classification of circulating blood cell clusters based on multi-channel flow cytometry imaging","year":2025,"lang":"en","type":"article","venue":"Engineering Applications of Artificial Intelligence","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Air Force Office of Scientific Research; U.S. Department of Energy; National Heart, Lung, and Blood Institute; Directorate for Mathematical and Physical Sciences; National Institutes of Health; National Science Foundation","keywords":"Blood flow; Flow cytometry; Pattern recognition (psychology); Blood cell; Cytometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0002216316,0.0001737838,0.0002019697,0.0006607454,0.00007048291,0.00009151413,0.0008310623,0.00003847525,0.000002990149],"category_scores_gemma":[0.0002046133,0.0002034972,0.0001111879,0.001597972,0.00007555565,0.0002598605,0.0001076521,0.0001107607,0.00001371447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004281804,"about_ca_system_score_gemma":0.00009173658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001349955,"about_ca_topic_score_gemma":5.42952e-7,"domain_scores_codex":[0.9985144,0.0000179785,0.0006083761,0.0003852758,0.0002548444,0.0002191273],"domain_scores_gemma":[0.9983708,0.0003220103,0.0002042546,0.0008451562,0.0001887718,0.00006903976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002991549,0.0009466857,0.0001958411,0.0004079486,0.00002454755,0.000001253072,0.0001500847,0.8262665,0.02903261,0.01809805,0.00001437428,0.1248591],"study_design_scores_gemma":[0.00004321242,0.00001413494,0.0004896394,0.0001384105,0.0000242458,6.013761e-7,0.00005804834,0.8535616,0.1447048,0.0008268961,0.00001009269,0.000128319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008745491,0.0001054245,0.9898682,0.000150561,0.0001107911,0.0003591981,0.00001412313,0.000273795,0.0003724006],"genre_scores_gemma":[0.848471,0.000001252758,0.1513481,0.00003352627,0.00001169134,0.0001040207,0.000007898682,0.00001293481,0.000009467364],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8397256,"threshold_uncertainty_score":0.8298376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751889989552063,"score_gpt":0.2649000304221472,"score_spread":0.2473811305266265,"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."}}