{"id":"W4392943772","doi":"10.1109/mosicom59118.2023.10458738","title":"Automating CT Diagnostic Image Quality Control Using Transfer Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Quality (philosophy); Image quality; Transfer of learning; Artificial intelligence; Control (management); Computer vision; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002180357,0.001117869,0.0004497379,0.0008161335,0.000251487,0.001269933,0.001518375,0.0009379566,0.001529622],"category_scores_gemma":[0.009445681,0.0002949793,0.000493561,0.000502501,0.0005909835,0.001440297,0.001207123,0.001528044,0.0006125561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668905,"about_ca_system_score_gemma":0.001553408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008502045,"about_ca_topic_score_gemma":0.006189543,"domain_scores_codex":[0.999306,0.0001602907,0.0000384909,0.0002088488,0.0001994405,0.0000870447],"domain_scores_gemma":[0.9970752,0.001256601,0.0004231194,0.0004161885,0.0007098287,0.0001190442],"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":[0.0006712452,0.0006389949,0.01301284,0.0002343837,0.0001669957,0.000172274,0.0001026474,0.4913796,0.02374329,0.001544145,0.004974724,0.4633588],"study_design_scores_gemma":[0.00002025229,0.0001211014,0.001211409,0.00001629208,0.00001774334,0.00005771431,0.00001459036,0.9806775,0.01593675,0.001269803,0.0006445571,0.00001222956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3951212,0.002747393,0.5764035,0.001575415,0.0002063227,0.0004455154,0.0006536812,0.01739207,0.005454926],"genre_scores_gemma":[0.9356129,0.0003202373,0.06163548,0.0002481479,0.00003754722,0.00005231486,0.0005449042,0.0001493733,0.001399081],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008502045,"threshold_uncertainty_score":0.01690507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0518208432308644,"score_gpt":0.3962096247390012,"score_spread":0.3443887815081368,"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."}}