{"id":"W3000624514","doi":"10.1016/j.clon.2019.12.009","title":"Patient-Derived Organoids: Promises, Hurdles and Potential Clinical Applications","year":2020,"lang":"en","type":"editorial","venue":"Clinical Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Medical Research Council; Institute of Cancer Research; Cancer Research UK; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; European Commission; Royal Marsden NHS Foundation Trust","keywords":"Medicine; Precision medicine; Colorectal cancer; Personalized medicine; Targeted therapy; Oncology; Scopus; Cancer; Bioinformatics; Computational biology; Internal medicine; Cancer research; MEDLINE; Pathology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005918127,0.0003754394,0.001065815,0.000032456,0.000120661,0.00005108564,0.0004232074,0.003288625,0.00003829317],"category_scores_gemma":[0.005917848,0.0003754166,0.00040852,0.0000714794,0.0007408178,0.000002772775,0.0008705173,0.001237915,0.00007729949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004687919,"about_ca_system_score_gemma":0.002393693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001503739,"about_ca_topic_score_gemma":0.0000527329,"domain_scores_codex":[0.9960892,0.0003916539,0.001627198,0.001302427,0.0002235629,0.000365917],"domain_scores_gemma":[0.9963851,0.001343041,0.0007659224,0.0006387531,0.0003427914,0.0005243757],"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":[0.0004809817,0.0004450548,0.0003385234,0.00004281908,0.0002426327,0.00002871337,0.000009409448,0.0000015768,0.002195979,0.00002038223,0.9323792,0.06381465],"study_design_scores_gemma":[0.002074497,0.004585979,0.0003759683,0.00001380563,0.0002869577,0.000005374081,0.0000273871,0.000006958252,0.0001913164,0.0001632019,0.9918617,0.0004068355],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.03290642,0.005868364,0.001834438,0.002354037,0.9519768,0.002108798,0.001532814,0.00007378797,0.001344541],"genre_scores_gemma":[0.01022193,0.02599348,0.003058757,0.00197258,0.9545467,0.0002821372,0.003555305,0.0001188064,0.0002503308],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.06340782,"threshold_uncertainty_score":0.9998698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0232601903168983,"score_gpt":0.3683545372046455,"score_spread":0.3450943468877472,"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."}}