{"id":"W4305056839","doi":"10.1117/12.2640989","title":"Malaria cell classification with residual neural network","year":2022,"lang":"en","type":"article","venue":"","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Malaria; Convolutional neural network; Artificial intelligence; Residual neural network; Computer science; Transfer of learning; Pattern recognition (psychology); Diagnosis of malaria; Residual; Artificial neural network; Blood smear; Deep learning; Machine learning; Plasmodium falciparum; Biology; Immunology; Algorithm","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":[0.00009016007,0.00007881798,0.00006056486,0.00003648441,0.0001940116,0.0002680323,0.0006720974,0.000006588205,0.00006431173],"category_scores_gemma":[0.000003963697,0.00006832322,0.00002120025,0.0003967588,0.00002679507,0.0005809419,0.0004078385,0.00008281892,0.00003150861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000024166,"about_ca_system_score_gemma":0.00006520445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001310276,"about_ca_topic_score_gemma":0.000002380078,"domain_scores_codex":[0.9990436,0.00004566123,0.00009667829,0.0002803113,0.0003119964,0.0002217911],"domain_scores_gemma":[0.9993831,0.00003115491,0.00004843036,0.0004385088,0.00002664094,0.0000721829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007137435,0.0007317865,0.03112936,0.0000176599,0.00003011298,0.0001489857,0.0002523187,0.05674456,0.000335533,0.6345581,0.2568126,0.01916759],"study_design_scores_gemma":[0.002538423,0.001489213,0.2774605,0.00001277078,0.00007095837,0.0002574604,0.0005363767,0.6180933,0.001524127,0.02055865,0.07592372,0.00153446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3149274,0.0005450479,0.08919106,0.01882054,0.001378955,0.0008148568,0.00002812034,0.002672035,0.571622],"genre_scores_gemma":[0.9778254,2.781497e-7,0.01770225,0.0009866147,0.0000485197,0.00003261833,0.00001179652,0.00000871054,0.003383797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.662898,"threshold_uncertainty_score":0.278614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503761458807757,"score_gpt":0.2096797100978606,"score_spread":0.194642095509783,"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."}}