{"id":"W2998955300","doi":"10.29173/hsi233","title":"CRISPR and TALEN: Facilitating Tailored Genomes of the Future","year":2017,"lang":"en","type":"article","venue":"Health Science Inquiry","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"CRISPR; Transcription activator-like effector nuclease; Genome editing; Computational biology; Genome; Biology; Computer science; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001960269,0.0005727406,0.0007197456,0.0006351168,0.0007595381,0.002634115,0.001394526,0.001691379,0.005863723],"category_scores_gemma":[0.002166798,0.0004499562,0.0004594075,0.0004842251,0.001762714,0.002468916,0.002495683,0.003179491,0.001161087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008753184,"about_ca_system_score_gemma":0.001205921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005999849,"about_ca_topic_score_gemma":0.000961828,"domain_scores_codex":[0.9992466,0.000197332,0.00002681979,0.000126131,0.0002895361,0.0001135651],"domain_scores_gemma":[0.999289,0.0003316556,0.00007628486,0.0001050756,0.00005632392,0.0001416556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005469393,0.0001707061,0.0008573158,0.0008523702,0.00009799471,0.000555812,0.0008494914,0.009199043,0.4910138,0.3264698,0.01921612,0.1501706],"study_design_scores_gemma":[0.0001405035,0.000381718,0.0009697977,0.0002057683,0.00008862476,0.0009945025,0.0007595323,0.01999247,0.4299324,0.168986,0.3773875,0.0001612527],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1457705,0.03585174,0.7104373,0.02869791,0.003353162,0.0004496203,0.002189296,0.008340174,0.06491038],"genre_scores_gemma":[0.5202007,0.0276512,0.4177717,0.004375545,0.0003895533,0.0002839878,0.001639172,0.0008921864,0.02679601],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005863723,"threshold_uncertainty_score":0.01961613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02631264069838381,"score_gpt":0.3830855437457636,"score_spread":0.3567729030473799,"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."}}