{"id":"W2566444561","doi":"10.1038/srep38968","title":"A CRISPR/Cas9 Functional Screen Identifies Rare Tumor Suppressors","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute; Occupational Cancer Research Centre; Institute for Research in Immunology and Cancer; McGill University","funders":"Canadian Cancer Society Research Institute","keywords":"CRISPR; Suppressor; Cas9; Computational biology; Biology; Computer science; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004520141,0.0001483386,0.0001149696,0.00008399703,0.0001773828,0.0001194709,0.0001283542,0.00006626248,0.0003069807],"category_scores_gemma":[0.000208428,0.0001094165,0.0001214193,0.0001256054,0.0001754897,0.0000103176,0.0001429331,0.00004198476,0.00004748251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001224921,"about_ca_system_score_gemma":0.00007969698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009346739,"about_ca_topic_score_gemma":0.00002954343,"domain_scores_codex":[0.9983548,0.00002101052,0.0002979471,0.0007034659,0.0003158287,0.0003069842],"domain_scores_gemma":[0.9989094,0.00001016687,0.00009581109,0.000711132,0.0001514775,0.0001220052],"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":[0.00001269842,0.0000184879,0.003440202,0.00000901899,0.00002153894,0.00007837608,0.00001560018,0.00007112802,0.9037402,0.00001350754,0.09180015,0.0007790764],"study_design_scores_gemma":[0.0001540361,0.00002690024,0.005516083,0.00002389342,0.00001235203,0.0003316672,0.00003301053,0.00001023592,0.8380021,0.0004667078,0.1552382,0.0001848191],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711628,0.0006662235,0.02038235,0.0002048061,0.006075237,0.0001848578,0.00001864805,0.0000491191,0.001255938],"genre_scores_gemma":[0.9799732,0.000008323079,0.0002670267,0.0000345077,0.0002820268,0.00002205948,0.00009382171,0.00002090243,0.01929811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06573807,"threshold_uncertainty_score":0.4461874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009601333199828277,"score_gpt":0.2661813204443528,"score_spread":0.2565799872445245,"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."}}