{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002343151,0.0001135072,0.000211484,0.00005528066,0.0001457472,0.00005941278,0.0001568854,0.00003767086,0.0007733211],"category_scores_gemma":[0.00008951857,0.00007563353,0.00002630371,0.0002547543,0.00002141595,0.00008620149,0.0001137006,0.0001293718,0.00001321329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004342712,"about_ca_system_score_gemma":0.0004046099,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03181344,"about_ca_topic_score_gemma":0.01610371,"domain_scores_codex":[0.9991525,0.00009759807,0.0001866742,0.0002459754,0.0001242157,0.0001930214],"domain_scores_gemma":[0.999284,0.0001406685,0.00004504808,0.0002132836,0.00001658627,0.0003003893],"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":[0.001343963,0.0005564572,0.3024375,0.0007493476,0.0004983886,0.0007424451,0.03986263,0.00009583154,0.00001045905,0.005376939,0.4541175,0.1942085],"study_design_scores_gemma":[0.003202252,0.000276545,0.2215523,0.00006674346,0.0001079224,0.000009204502,0.001077708,0.0004451557,0.000008736778,0.00006017003,0.773106,0.00008725392],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02936644,0.0004273639,0.0001384462,0.9580196,0.00008195759,0.002833063,0.00004043494,0.00003496884,0.0090577],"genre_scores_gemma":[0.8215616,0.002186982,0.0005108786,0.1738925,0.0001140855,0.0004095697,0.00007936475,0.0000145554,0.001230495],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7921951,"threshold_uncertainty_score":0.9746338,"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."}}