{"id":"W4386714871","doi":"10.3390/bioengineering10091077","title":"The Performance of a Deep Learning-Based Automatic Measurement Model for Measuring the Cardiothoracic Ratio on Chest Radiographs","year":2023,"lang":"en","type":"article","venue":"Bioengineering","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Medicine; Radiography; Intraclass correlation; Interquartile range; Radiology; Nuclear medicine; Pleural effusion; Surgery","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":[],"consensus_categories":[],"category_scores_codex":[0.001434892,0.0001655434,0.000236705,0.0002020578,0.0002541108,0.00003172885,0.0001583128,0.0000471824,9.83525e-7],"category_scores_gemma":[0.0006482911,0.0001072734,0.0001957558,0.000539096,0.0000476064,0.00003190126,0.00002173868,0.0001786428,0.000005035144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002002,"about_ca_system_score_gemma":0.0001027413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005534876,"about_ca_topic_score_gemma":0.000005118553,"domain_scores_codex":[0.9986431,0.00003006343,0.0002677531,0.0001869596,0.0005629175,0.0003092159],"domain_scores_gemma":[0.9988964,0.0004293893,0.00007768266,0.0003901899,0.0001474042,0.00005891371],"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":[0.00004229374,0.00002118288,0.0008326364,0.0006861813,0.00009888475,0.00000117791,0.000297479,0.9812199,0.007413751,0.00001512261,0.000158942,0.009212418],"study_design_scores_gemma":[0.0005030991,0.0001684787,0.007197032,0.0004441454,0.0001070622,0.000001622314,0.00004157503,0.977653,0.01239258,0.00000142481,0.001381972,0.0001080071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8682386,0.001357679,0.1183533,0.008766596,0.0004294117,0.001938049,0.000004314165,0.0008909889,0.0000210809],"genre_scores_gemma":[0.9986584,0.00007773846,0.0006006029,0.0001950888,0.00007891255,0.0003136394,0.000003702666,0.00004844485,0.00002347851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1304198,"threshold_uncertainty_score":0.4374481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0481505766734326,"score_gpt":0.2800269968327865,"score_spread":0.2318764201593539,"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."}}