{"id":"W3114862706","doi":"","title":"Infrared Imaging Tools for Necrotizing Enterocolitis (NEC) Diagnosis Guided by RGB-D Sensing","year":2019,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Infant Nutrition and Health","field":"Nursing","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; Carleton University; University of Ottawa","funders":"","keywords":"Multispectral image; RGB color model; Artificial intelligence; Computer vision; Computer science; Necrotizing enterocolitis; Segmentation; Thermography; Radiance; Remote sensing; Infrared; Medicine; Geography; Optics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003614183,0.0002857634,0.0004242562,0.0001886891,0.0003958084,0.0006004203,0.0001655981,0.0001295493,0.0001135142],"category_scores_gemma":[0.0003889449,0.0003187747,0.0001728719,0.0002334009,0.00005370674,0.001433384,0.00006674702,0.0002320243,0.0001023495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002526621,"about_ca_system_score_gemma":0.00002576877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005813173,"about_ca_topic_score_gemma":0.00000192164,"domain_scores_codex":[0.9978164,0.00001283517,0.0005542014,0.0005438656,0.0002668227,0.0008058442],"domain_scores_gemma":[0.9987403,0.0002236133,0.0002470515,0.0001509478,0.0004492643,0.0001888882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004182248,0.0001474244,0.06604532,0.001936332,0.00003939665,0.000004868504,0.003944086,7.784079e-7,0.08102427,0.002550022,0.8110687,0.03282057],"study_design_scores_gemma":[0.005183632,0.0003808165,0.003427578,0.001716637,0.00008302426,0.0001661256,0.00363746,0.003681474,0.1599905,0.004849933,0.8158609,0.001021886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964226,0.0004129784,0.0003124756,0.007602146,0.001553811,0.003079098,0.000105125,0.0005684311,0.02213995],"genre_scores_gemma":[0.9802976,0.00006263803,0.007466491,0.0101899,0.0005591669,0.0002227395,0.0001012624,0.0001179889,0.0009822478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07896627,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253623711995534,"score_gpt":0.2933357264465717,"score_spread":0.2707994893266163,"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."}}