{"id":"W3037012925","doi":"10.1136/esmoopen-2020-000820","title":"ESMO Management and treatment adapted recommendations in the COVID-19 era: Lung cancer","year":2020,"lang":"en","type":"article","venue":"ESMO Open","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Merck Sharp and Dohme; Daiichi-Sankyo; Cancer Research UK; Clovis Oncology; Merck KGaA; Boehringer Ingelheim; Celgene; GlaxoSmithKline; Novartis; Pfizer; Takeda Pharmaceutical Company; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Pandemic; Flexibility (engineering); Health care; Coronavirus disease 2019 (COVID-19); Economic shortage; Medicine; Cancer; Scale (ratio); Business; Lung cancer; Intensive care medicine; Risk analysis (engineering); Medical emergency; Political science; Economics; Disease; Law; Oncology; Pathology; Geography","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":[0.008956483,0.0005305108,0.0006086415,0.001228769,0.001952676,0.003582147,0.002148804,0.007963656,0.009952667],"category_scores_gemma":[0.03443156,0.000309333,0.001768418,0.0007389681,0.001254622,0.002861376,0.004503905,0.009709576,0.006457724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00380404,"about_ca_system_score_gemma":0.01677835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01089202,"about_ca_topic_score_gemma":0.02347479,"domain_scores_codex":[0.9919555,0.004359056,0.001133159,0.0003078658,0.001446125,0.0007984279],"domain_scores_gemma":[0.9884369,0.002514896,0.0008932754,0.0003847123,0.004585718,0.003184508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008054653,0.0002368966,0.002881161,0.001347804,0.00004633177,0.001296789,0.001504963,0.001427803,0.000554656,0.0121937,0.7876357,0.1907938],"study_design_scores_gemma":[0.00004653126,0.0001041319,0.002691462,0.003729152,0.00003891913,0.0005917611,0.001254979,0.0004995383,0.0002387943,0.00745029,0.9833024,0.00005201958],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.006157783,0.01961299,0.02192243,0.8294997,0.02492509,0.001682408,0.001451052,0.0007803466,0.09396829],"genre_scores_gemma":[0.1249191,0.1071414,0.1847386,0.4329884,0.0348717,0.005635759,0.006255231,0.0007997427,0.10265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01089202,"threshold_uncertainty_score":0.04736692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1989447492378444,"score_gpt":0.4751496173103141,"score_spread":0.2762048680724697,"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."}}