{"id":"W4303444951","doi":"10.1145/3549555.3549581","title":"Chest Diseases Classification Using CXR and Deep Ensemble Learning","year":2022,"lang":"en","type":"article","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"New Brunswick Innovation Foundation; Compute Canada","keywords":"Convolutional neural network; Deep learning; Artificial intelligence; Computer science; Ensemble learning; Machine learning; Pattern recognition (psychology)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001123453,0.00007122075,0.0001180694,0.00008966771,0.0002581066,0.00002252636,0.00003289509,0.00001877579,0.0006118094],"category_scores_gemma":[0.0001989102,0.00007137264,0.00003035961,0.0001715809,0.00003117556,0.00004868995,0.00008703932,0.0001500581,0.00001388388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001837321,"about_ca_system_score_gemma":0.00008924658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001092829,"about_ca_topic_score_gemma":0.000006860564,"domain_scores_codex":[0.9993006,0.00005500184,0.0001104292,0.0002134145,0.0001917186,0.0001288511],"domain_scores_gemma":[0.9995329,0.0001584579,0.00004567341,0.0001418454,0.00002955447,0.00009155664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002426316,0.0008744064,0.7874506,0.0004121907,0.000106909,0.0001174305,0.00187711,0.004905493,0.1149634,0.00149847,0.0103328,0.0772185],"study_design_scores_gemma":[0.001508279,0.0003178103,0.420808,0.00005751603,0.0003392223,0.0001070049,0.002447036,0.2215534,0.001251212,0.0001275574,0.3511959,0.0002870528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982883,0.000649755,0.001968264,0.01291045,0.00009796361,0.0002310473,0.00000189752,0.000159904,0.001097762],"genre_scores_gemma":[0.9932115,0.00003144626,0.0009435991,0.004482826,0.00006971811,0.00001772147,0.00001938064,0.00001875927,0.001205026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3666426,"threshold_uncertainty_score":0.6698883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05979404341485998,"score_gpt":0.3312037593863626,"score_spread":0.2714097159715026,"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."}}