{"id":"W4394939731","doi":"10.1007/978-3-031-47724-9_6","title":"Pre-trained Deep Learning Models for Chest X-Rays’ Classification: Views and Age-Groups","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"CMC Microsystems (Canada)","funders":"","keywords":"Artificial intelligence; Deep learning; Computer science","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":[0.0006119437,0.0005284708,0.001131306,0.0002364539,0.0001275193,0.0002159499,0.00009903367,0.000987565,0.000009719907],"category_scores_gemma":[0.0001372324,0.0004391391,0.0001642705,0.00009377728,0.0001257941,0.00005256787,0.00006682501,0.001076572,0.000002347933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001850775,"about_ca_system_score_gemma":0.00005770845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004490964,"about_ca_topic_score_gemma":0.0002444613,"domain_scores_codex":[0.997788,0.00004733637,0.0006844616,0.0008693805,0.0002471331,0.0003637078],"domain_scores_gemma":[0.9978226,0.001282541,0.0002521897,0.0003893827,0.00009434265,0.0001589244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005005682,0.00009011305,0.000650586,0.01646362,0.0008448535,0.0003603402,0.005466647,0.7759911,0.0001302466,0.04915404,0.003258677,0.1470892],"study_design_scores_gemma":[0.0006889059,0.0002264898,0.0001257193,0.005381505,0.0003725619,0.00007881386,0.00001583235,0.7584442,7.021201e-7,0.006397259,0.2278686,0.0003994372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003776975,0.2728035,0.6993389,0.007370642,0.002365201,0.006331117,0.00003240387,0.0004264136,0.01095415],"genre_scores_gemma":[0.960439,0.006961965,0.0006042306,0.002335816,0.0042968,0.0004886442,0.0003802054,0.0003003124,0.02419301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9600613,"threshold_uncertainty_score":0.999806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06540825786940448,"score_gpt":0.3012872410133912,"score_spread":0.2358789831439868,"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."}}