{"id":"W4255365098","doi":"10.3410/f.717969062.793517055","title":"Faculty Opinions recommendation of Multiplex genome engineering using CRISPR/Cas systems.","year":2016,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"CRISPR; Multiplex; Computational biology; Genome engineering; Genome; Multiplex polymerase chain reaction; Computer science; Biology; Data science; Genetics; Genome editing; Gene; Polymerase chain reaction","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":[0.001932449,0.002688492,0.002295285,0.006209034,0.0008283664,0.003650669,0.003192512,0.002968217,0.133732],"category_scores_gemma":[0.01344906,0.0007594878,0.001822477,0.008837246,0.0004111994,0.002249803,0.0028717,0.001968802,0.162194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001882401,"about_ca_system_score_gemma":0.004484713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02268448,"about_ca_topic_score_gemma":0.05383277,"domain_scores_codex":[0.9976596,0.0003300945,0.000343351,0.0006253287,0.0007207851,0.0003208057],"domain_scores_gemma":[0.9936631,0.00162788,0.0009480815,0.001171536,0.001563941,0.001025413],"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":[0.00009246142,0.00001845089,0.001103406,0.0009297148,0.00004021137,0.00001666703,0.00001037077,0.0001277783,0.00009348826,0.0002120845,0.9949309,0.00242448],"study_design_scores_gemma":[0.0003147594,0.00002312771,0.004403972,0.0005921855,0.00006669772,0.00005058244,0.00003976206,0.0003644816,0.0004067024,0.0009852619,0.9927211,0.00003134935],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000060122,0.00008255076,0.00003776188,0.00007352692,0.00002230417,0.000008037784,0.9988359,0.0002811498,0.0005986154],"genre_scores_gemma":[0.000280319,0.000101243,0.0001786802,0.00008637674,0.00001124968,0.00003990797,0.9982481,0.00007645778,0.0009777476],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.133732,"threshold_uncertainty_score":0.4473782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505420986849337,"score_gpt":0.364837083281268,"score_spread":0.3397828734127746,"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."}}