{"id":"W3147518691","doi":"","title":"Anti-CRISPRs and CRISPR-Cas: Characterization and Biotechnology","year":2019,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"CRISPR; Biotechnology; Biology; Computational biology; Genetics; 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":[0.0004919161,0.0003848317,0.0002408019,0.000775381,0.000214169,0.0008241005,0.0006756734,0.0004278643,0.0016521],"category_scores_gemma":[0.0004828343,0.0002215667,0.000377064,0.00053644,0.0003133735,0.0004317822,0.0003203065,0.0009856184,0.001156443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003878207,"about_ca_system_score_gemma":0.0003891313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005339348,"about_ca_topic_score_gemma":0.0003603328,"domain_scores_codex":[0.9996717,0.00004462352,0.00002496249,0.00007166193,0.0001393111,0.00004784073],"domain_scores_gemma":[0.9996629,0.00005486095,0.00007304361,0.00003622866,0.0001130252,0.00006000691],"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":[0.00009357316,0.0001511124,0.002046819,0.0002188124,0.00001628441,0.0001752457,0.00006694697,0.000686268,0.9636377,0.002269457,0.001147017,0.02949067],"study_design_scores_gemma":[0.00001096801,0.000303952,0.005641324,0.00002777081,0.00002059908,0.0009694625,0.00006721643,0.00362197,0.9439922,0.001061957,0.04425553,0.00002720115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8068519,0.03081256,0.1259956,0.002953837,0.000524879,0.0005554946,0.00518205,0.0008132873,0.02631052],"genre_scores_gemma":[0.8387519,0.01548569,0.1074936,0.0007112242,0.0001740211,0.000268227,0.007859433,0.0001659875,0.02909002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0016521,"threshold_uncertainty_score":0.005526781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004270571980771745,"score_gpt":0.2461219186983523,"score_spread":0.2418513467175805,"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."}}