{"id":"W4404095986","doi":"10.1183/13993003.congress-2024.pa4995","title":"The Hidden Gem: The Costa Rica Lung Transplant Program","year":2024,"lang":"en","type":"article","venue":"Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005808129,0.0001405892,0.00007548099,0.0003121364,0.0004186099,0.0006270846,0.000400382,0.0002003015,0.004183907],"category_scores_gemma":[0.0006214203,0.00005194681,0.0001126807,0.0004674532,0.0001935478,0.0002095196,0.0007847385,0.0002763728,0.0008182508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649584,"about_ca_system_score_gemma":0.003678804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06774378,"about_ca_topic_score_gemma":0.1075488,"domain_scores_codex":[0.9998471,0.00004947963,0.000008154191,0.0000178045,0.00003800833,0.00003953553],"domain_scores_gemma":[0.9994832,0.00004695897,0.00008613765,0.00005640636,0.0001139779,0.0002132291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000277603,0.0003010736,0.6981092,0.0003468753,0.00007023294,0.00101737,0.0008057567,0.0007403712,0.002203454,0.002416893,0.08481856,0.2088926],"study_design_scores_gemma":[0.00005854452,0.0001102587,0.9053341,0.000156647,0.00003059247,0.0004761872,0.0006969102,0.001231211,0.0004768143,0.0002459596,0.09117233,0.00001038368],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.848032,0.005939107,0.001602923,0.01803761,0.000311097,0.0007163449,0.01937821,0.0005685416,0.1054142],"genre_scores_gemma":[0.9480516,0.00285655,0.002618139,0.004808289,0.0002269209,0.000270682,0.007302316,0.0000592763,0.03380616],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.06774378,"threshold_uncertainty_score":0.1346989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100441738018383,"score_gpt":0.3516314362320571,"score_spread":0.3306270188518732,"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."}}