{"id":"W3214304248","doi":"10.1073/pnas.2115116118","title":"CRISPR-SID: Identifying EZH2 as a druggable target for desmoid tumors via in vivo dependency mapping","year":2021,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Chromatin Remodeling and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"National Cancer Institute; Bijzonder Onderzoeksfonds UGent; Stand Up To Cancer; Vlaamse regering; Universiteit Gent; Fonds Wetenschappelijk Onderzoek; Agentschap Innoveren en Ondernemen; Kom op tegen Kanker; Agentschap voor Innovatie door Wetenschap en Technologie; Desmoid Tumor Research Foundation","keywords":"CRISPR; Druggability; Wnt signaling pathway; Computational biology; Biology; Cancer research; Carcinogenesis; Genome editing; Genetics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007902261,0.00007541956,0.0001141464,0.00006767505,0.0001292728,0.00002201878,0.0003797393,0.00007964936,0.00001662382],"category_scores_gemma":[0.0004292955,0.00006168053,0.00008171779,0.0003399758,0.0001532565,0.00002405617,0.0001271252,0.00007648566,3.75922e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002170968,"about_ca_system_score_gemma":0.0001100435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001381496,"about_ca_topic_score_gemma":6.524065e-7,"domain_scores_codex":[0.9988686,0.000005111467,0.000270256,0.000269621,0.0004321384,0.0001542174],"domain_scores_gemma":[0.9994701,0.00002368359,0.0002065318,0.00001026896,0.0002664558,0.00002293378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009189851,0.00002211125,0.002112429,0.00009178984,0.000008869242,1.151619e-8,0.00009140276,0.000424825,0.9956474,0.0009899825,0.000425038,0.0001769751],"study_design_scores_gemma":[0.000190548,0.00002681549,0.001139389,0.0001161197,0.00000421072,0.00001463317,0.000391404,0.002109275,0.9616643,0.03378769,0.000479146,0.00007648476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947625,0.000760072,0.0001335897,0.0006375314,0.00002685182,0.0001273181,0.0000108192,0.000003757359,0.003537533],"genre_scores_gemma":[0.9924923,0.00005291909,0.006701302,0.0002237333,0.00007670389,0.00002023617,6.213169e-7,0.000004847475,0.0004273506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0339831,"threshold_uncertainty_score":0.2515259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03508239185839815,"score_gpt":0.3223301042785175,"score_spread":0.2872477124201194,"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."}}