{"id":"W4398775429","doi":"10.1038/s41598-024-62890-7","title":"Association between pre-treatment computed tomography findings and post-treatment persistent decrease in lung perfusion blood volume","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eisai Canada","keywords":"Medicine; Perfusion; Thrombus; Perfusion scanning; Pulmonary embolism; Radiology; Lung; Blood volume; Angiography; Computed tomography; Pulmonary angiography; Cardiology; Internal medicine; Nuclear medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003222739,0.0002379695,0.0003399392,0.0005611184,0.0002250702,0.0004318021,0.000292035,0.0004908948,0.001373946],"category_scores_gemma":[0.003937638,0.0001730999,0.0002608872,0.0004353408,0.0003492011,0.0003849323,0.000209371,0.0006232594,0.0002025321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185544,"about_ca_system_score_gemma":0.0002252485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008926543,"about_ca_topic_score_gemma":0.001227258,"domain_scores_codex":[0.9995145,0.0001116629,0.00007541219,0.00008878866,0.0001093336,0.0001002836],"domain_scores_gemma":[0.9968709,0.001023071,0.001363453,0.0001871866,0.0002490111,0.0003064958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000266506,0.00002654661,0.996686,0.000008295326,0.000021403,0.0004851221,0.00002737305,0.00004673137,0.0006690316,0.00001083897,0.0000258395,0.001726364],"study_design_scores_gemma":[0.000005872799,0.0002592025,0.9965244,0.000003510971,0.0000249575,0.002627654,0.00005580747,0.000164006,0.0002383708,0.00001020403,0.00008288947,0.000003050166],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990423,0.0004090445,0.0001249302,0.00003058598,0.000003739085,0.000004820749,0.00003706615,0.000003486979,0.0003440129],"genre_scores_gemma":[0.9997954,0.00005235877,0.00003863596,0.000009168509,0.000008883102,0.000002192447,0.00005762707,0.000001070474,0.00003459235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001373946,"threshold_uncertainty_score":0.004596293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008987594698511974,"score_gpt":0.2494933503546905,"score_spread":0.2405057556561785,"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."}}