{"id":"W2172221636","doi":"10.1109/ccece.2006.277785","title":"A High Throughput Screening Algorithm for Leukemia Cells","year":2006,"lang":"en","type":"article","venue":"","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Alberta; University of Calgary","keywords":"Throughput; Computer science; Leukemia; Algorithm; Biology; Genetics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008044779,0.0006659362,0.000733437,0.001322225,0.0007039302,0.0009164835,0.0009924457,0.0007168982,0.002103029],"category_scores_gemma":[0.001748178,0.0003915633,0.0005860053,0.0007308697,0.0003829052,0.0007963114,0.0007338693,0.0006012216,0.001689629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007406545,"about_ca_system_score_gemma":0.0008902879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001496133,"about_ca_topic_score_gemma":0.001272511,"domain_scores_codex":[0.9992695,0.000107475,0.00005038683,0.0001485369,0.0003593983,0.00006465731],"domain_scores_gemma":[0.9991859,0.0002941008,0.000074122,0.00009375173,0.0003188098,0.00003329144],"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":[0.0005769625,0.0001689372,0.003074927,0.0002048436,0.00008300987,0.0003295334,0.0002322358,0.0348279,0.3496987,0.008026804,0.006571765,0.5962043],"study_design_scores_gemma":[0.0001022481,0.0002764605,0.002620257,0.00002713069,0.00006739623,0.0007286113,0.00005227921,0.6633111,0.3083248,0.00486313,0.01954938,0.00007710821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01017043,0.0001020053,0.9850772,0.00006428653,0.00002262773,0.0001129452,0.00008201127,0.003775243,0.0005932478],"genre_scores_gemma":[0.05431316,0.0001055762,0.9433777,0.00006734984,0.00001265027,0.0002579598,0.0003452285,0.0001244385,0.001395955],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002103029,"threshold_uncertainty_score":0.007035315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00986299752985368,"score_gpt":0.2230716200583818,"score_spread":0.2132086225285282,"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."}}