{"id":"W4252122577","doi":"10.3410/f.718206644.793489639","title":"Faculty Opinions recommendation of Genetic screens in human cells using the CRISPR-Cas9 system.","year":2014,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"CRISPR; Cas9; Computational biology; Genetics; Biology; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001910575,0.002957411,0.002176112,0.005509211,0.0009394662,0.003021429,0.003765038,0.003893311,0.08496666],"category_scores_gemma":[0.01171115,0.0008057016,0.00208757,0.006582331,0.0004493446,0.001693501,0.002229155,0.00224452,0.1076688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002087145,"about_ca_system_score_gemma":0.004233221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02764205,"about_ca_topic_score_gemma":0.06632249,"domain_scores_codex":[0.9979182,0.0003266071,0.0002926099,0.0005647501,0.000628855,0.0002689398],"domain_scores_gemma":[0.9944728,0.00176586,0.0005972651,0.001055649,0.001443815,0.0006646318],"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":[0.00007873183,0.0000264567,0.000825382,0.0007761491,0.00004083206,0.00001929944,0.000008127967,0.0001471401,0.0001276548,0.0001494974,0.9956378,0.002163009],"study_design_scores_gemma":[0.0005626301,0.00004012193,0.00636406,0.0005730456,0.0001146529,0.00009119442,0.00005893173,0.0009035725,0.0008186298,0.001098722,0.9893221,0.00005238329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001205775,0.0001031138,0.00006126059,0.00009155361,0.00003237472,0.00001682026,0.9985772,0.0003253593,0.0006716925],"genre_scores_gemma":[0.0003279896,0.0000804579,0.000252532,0.00008363849,0.00001031342,0.00005583637,0.9983715,0.00004602134,0.0007716056],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08496666,"threshold_uncertainty_score":0.2842418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02832306970017895,"score_gpt":0.3231449770857195,"score_spread":0.2948219073855406,"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."}}