{"id":"W4283080659","doi":"10.3390/diagnostics12061482","title":"COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans","year":2022,"lang":"en","type":"article","venue":"Diagnostics","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Jaccard index; Artificial intelligence; Segmentation; Coronavirus disease 2019 (COVID-19); Deep learning; Computer science; Hounsfield scale; Nuclear medicine; Pattern recognition (psychology); Medicine; Computed tomography; Radiology; Pathology","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":[0.0008923286,0.0009812593,0.0004786439,0.0009399878,0.0002917431,0.0006799135,0.001572873,0.0009863287,0.003076908],"category_scores_gemma":[0.002170705,0.0003145003,0.0007799871,0.0004377204,0.0002680813,0.0007011704,0.001234777,0.0008517068,0.0006152062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128235,"about_ca_system_score_gemma":0.001201499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01184688,"about_ca_topic_score_gemma":0.01534414,"domain_scores_codex":[0.9997335,0.00004923073,0.00001620065,0.0001128348,0.00005091706,0.0000373092],"domain_scores_gemma":[0.9995695,0.000162661,0.000067215,0.00006684743,0.00008920333,0.00004453143],"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":[0.00166853,0.0005286413,0.04576506,0.000517666,0.0005978237,0.001458435,0.0003386577,0.3296565,0.02168612,0.004016756,0.04637717,0.5473886],"study_design_scores_gemma":[0.00005310061,0.0001034785,0.003782518,0.00001869487,0.00004005279,0.0002095256,0.00001852474,0.9873122,0.004831895,0.001538487,0.00206913,0.00002234744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.365311,0.001283156,0.572935,0.001197083,0.0002047232,0.0008057696,0.007840567,0.04623041,0.004192361],"genre_scores_gemma":[0.7823668,0.0003027732,0.2052162,0.0004690367,0.0000865154,0.0003255655,0.008251465,0.0005328542,0.002448781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01184688,"threshold_uncertainty_score":0.02355582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0354414570866724,"score_gpt":0.3099345963737707,"score_spread":0.2744931392870983,"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."}}