{"id":"W4394411276","doi":"10.6084/m9.figshare.21220145","title":"Additional file 5 of Liquid biopsy using ascitic fluid and pleural effusion supernatants for genomic profiling in gastrointestinal and lung cancers","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pleural effusion; Pleural fluid; Liquid biopsy; Lung; Medicine; Pathology; Profiling (computer programming); Ascitic fluid; Effusion; Internal medicine; Computer science; Ascites; Surgery; Cancer","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001516071,0.001556854,0.001725835,0.002092369,0.000751059,0.002189731,0.002180885,0.002190851,0.5220903],"category_scores_gemma":[0.01659199,0.0006948235,0.001461213,0.003082776,0.0003885227,0.001330175,0.001351194,0.001413938,0.1034952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358601,"about_ca_system_score_gemma":0.001909839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009001846,"about_ca_topic_score_gemma":0.01682684,"domain_scores_codex":[0.9990545,0.0001481531,0.0001555589,0.0003426967,0.000162796,0.0001362716],"domain_scores_gemma":[0.9904938,0.006610991,0.0006487582,0.0008571873,0.001023937,0.0003652858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003780436,0.00006945221,0.003236315,0.00329125,0.0001249901,0.0000740908,0.00003398626,0.0005966694,0.0001939089,0.0005230395,0.9870172,0.004461089],"study_design_scores_gemma":[0.004903246,0.0001886246,0.0286369,0.00324934,0.0003961431,0.0005558337,0.0001740343,0.001778429,0.001077666,0.00811928,0.9507954,0.0001251634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007065161,0.00002107732,0.00004601976,0.00003225979,0.000007605991,0.00001224908,0.9995587,0.00008217292,0.0001691879],"genre_scores_gemma":[0.001486125,0.00006121525,0.0004468205,0.000146023,0.00001990244,0.0002504644,0.996482,0.0001258925,0.0009815143],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5220903,"threshold_uncertainty_score":0.6816802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835227697407041,"score_gpt":0.2579731884748745,"score_spread":0.2396209115008041,"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."}}