{"id":"W3144948800","doi":"10.18280/ts.380117","title":"Classification of Pneumonia Cell Images Using Improved ResNet50 Model","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pneumonia; Medical diagnosis; Lung; Computer science; Bacterial pneumonia; Disease; Artificial intelligence; Imaging technique; Medicine; Pattern recognition (psychology); Radiology; Pathology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002337268,0.0001512125,0.0002774932,0.0001075952,0.00006007399,0.00002337245,0.00008253463,0.00007418419,0.0002207971],"category_scores_gemma":[0.00005258286,0.0001532975,0.000119572,0.0002232019,0.00006127814,0.00008811431,0.00004483572,0.0001330517,0.000006816365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731094,"about_ca_system_score_gemma":0.0004546106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005117177,"about_ca_topic_score_gemma":0.00000651083,"domain_scores_codex":[0.9986234,0.00005238398,0.0004211388,0.0003421562,0.0003359501,0.0002249677],"domain_scores_gemma":[0.9990363,0.00009798561,0.0001682436,0.0003169067,0.0002772967,0.0001032734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007389234,0.0005430701,0.001638558,0.0002514699,0.00003485083,0.00001892225,0.0002435308,0.002716568,0.9917852,0.00007440241,0.001339028,0.001280473],"study_design_scores_gemma":[0.001706349,0.0001422527,0.01748852,0.0001763074,0.0002469493,0.00001023106,0.000112414,0.4652355,0.5135993,0.0001014353,0.001020227,0.000160469],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690788,0.000259278,0.02315974,0.00653044,0.00007505638,0.000371351,0.00003683416,0.00006841038,0.0004201343],"genre_scores_gemma":[0.9859012,0.00003193595,0.0115852,0.002008698,0.0001017671,0.00001713162,0.00004554158,0.00003011384,0.0002784043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4781859,"threshold_uncertainty_score":0.6251293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05531974426029505,"score_gpt":0.3176191492742359,"score_spread":0.2622994050139408,"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."}}