{"id":"W4313551974","doi":"10.1016/j.healun.2022.12.024","title":"Triaging donor lungs based on a microaspiration signature that predicts adverse recipient outcome","year":2023,"lang":"en","type":"article","venue":"The Journal of Heart and Lung Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Toronto General Hospital; University Health Network","funders":"","keywords":"Medicine; Contraindication; Lung; Transplantation; Lung transplantation; Cohort; Gastroenterology; Internal medicine; Retrospective cohort study; Surgery; Urology; Pathology","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":[0.0009343201,0.0003822897,0.0006417279,0.0008012597,0.0003356978,0.001431073,0.0004221731,0.0007228364,0.0008994695],"category_scores_gemma":[0.001823096,0.0001388291,0.0003736308,0.0005687049,0.000265751,0.0005865828,0.0005676194,0.0008175252,0.0004178566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002765046,"about_ca_system_score_gemma":0.0003702576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002921316,"about_ca_topic_score_gemma":0.0007843426,"domain_scores_codex":[0.9994584,0.0001236783,0.00006936314,0.0001226927,0.0001337129,0.0000922143],"domain_scores_gemma":[0.9987992,0.000219239,0.000445528,0.00009949904,0.0001760548,0.0002604374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008155899,0.0001556912,0.9666349,0.00003585404,0.0001265827,0.0003000247,0.00007622332,0.0002769451,0.008770442,0.0001316794,0.0007565371,0.02191958],"study_design_scores_gemma":[0.00006330129,0.001205185,0.9775681,0.00007058645,0.0002655033,0.002933542,0.0003969044,0.006205234,0.00866794,0.0007023359,0.001875156,0.00004610479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947504,0.0008521709,0.002043477,0.0003168916,0.0001263712,0.00007074208,0.0002987567,0.00003781195,0.001503333],"genre_scores_gemma":[0.9968253,0.0002397459,0.00157506,0.0002036186,0.0001359229,0.00004628917,0.0005610177,0.00000710515,0.0004058905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001431073,"threshold_uncertainty_score":0.004941225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03822409812179308,"score_gpt":0.3291225223422409,"score_spread":0.2908984242204479,"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."}}