{"id":"W2738903728","doi":"10.7554/elife.28129","title":"CRISPR-mediated genetic interaction profiling identifies RNA binding proteins controlling metazoan fitness","year":2017,"lang":"en","type":"article","venue":"eLife","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"NIH Office of the Director; Natural Sciences and Engineering Research Council of Canada; University of Toronto; National Institutes of Health; Harvard University","keywords":"CRISPR; RNA-binding protein; Biology; Genetics; Computational biology; RNA; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002100338,0.0003634533,0.0002978659,0.0006560667,0.000238164,0.000520516,0.0002883254,0.0003638295,0.0007972232],"category_scores_gemma":[0.0002240892,0.0002272015,0.0002620671,0.0002597951,0.0002917614,0.0001769779,0.0003954507,0.0004433216,0.0003484119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000537554,"about_ca_system_score_gemma":0.0002434154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009457015,"about_ca_topic_score_gemma":0.002565149,"domain_scores_codex":[0.9997261,0.00001831845,0.00002051288,0.00008804184,0.0001028212,0.00004418768],"domain_scores_gemma":[0.9998598,0.00003119048,0.00005321438,0.00001579469,0.00001564151,0.00002441712],"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":[0.00002030528,0.000004506739,0.0007539933,0.00001441501,0.000004604058,0.00002405134,0.000007688889,0.0001236717,0.9974169,0.00008047401,0.00002549672,0.001523958],"study_design_scores_gemma":[0.000007988328,0.00007255786,0.02913556,0.000007629039,0.0000360886,0.0002479585,0.00003889454,0.004794384,0.9630001,0.0001573541,0.002487349,0.00001413048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774744,0.0007870012,0.01687757,0.00008991887,0.00001455052,0.00003233312,0.001677448,0.00057916,0.002467596],"genre_scores_gemma":[0.9856372,0.0004798188,0.01114177,0.00006514464,0.000003773583,0.00003392531,0.0009110351,0.0001022444,0.001625001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009457015,"threshold_uncertainty_score":0.00390029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01538132085201758,"score_gpt":0.3234126774974656,"score_spread":0.308031356645448,"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."}}