{"id":"W4377234461","doi":"10.18280/ts.400201","title":"Evaluation of Deep Transfer Learning Methodologies on the COVID-19 Radiographic Chest Images","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Radiography; Transfer of learning; Deep learning; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Radiology; Medicine; Artificial intelligence; Computer science; Virology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01000528,0.0001831853,0.0003071036,0.0004378576,0.0001818009,0.00002337141,0.0001571618,0.00007597973,0.001294177],"category_scores_gemma":[0.003143477,0.0001290492,0.0002137331,0.0008873027,0.0001974202,0.0000533036,0.00002376987,0.0002628036,0.00003232866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001801753,"about_ca_system_score_gemma":0.0002406767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007651484,"about_ca_topic_score_gemma":0.00001624194,"domain_scores_codex":[0.9964476,0.001296765,0.0003600239,0.0003253767,0.001295563,0.000274699],"domain_scores_gemma":[0.9955454,0.003802503,0.00007500338,0.0002479511,0.0002191904,0.0001099546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001394302,0.001090115,0.03488695,0.001437811,0.001998838,0.0001038325,0.01809929,0.365242,0.2831213,0.002597184,0.0413893,0.248639],"study_design_scores_gemma":[0.02059927,0.005648861,0.5666543,0.0007795703,0.007595244,0.000053774,0.008841942,0.1287897,0.1736723,0.006835306,0.07922432,0.001305502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8770823,0.0003986774,0.01775867,0.1022479,0.0001460883,0.001594115,0.00001446254,0.0004483078,0.0003094622],"genre_scores_gemma":[0.9913498,0.0001476467,0.0004042023,0.007675978,0.0001092059,0.0002175516,0.00003691387,0.00002752335,0.00003122655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5317673,"threshold_uncertainty_score":0.9996188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2234753471708089,"score_gpt":0.40992655255014,"score_spread":0.1864512053793312,"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."}}