{"id":"W2897791282","doi":"10.1089/crispr.2018.0043","title":"A Unified Resource for Tracking Anti-CRISPR Names","year":2018,"lang":"en","type":"letter","venue":"The CRISPR Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Toronto","funders":"National Institute of General Medical Sciences; Novo Nordisk Fonden","keywords":"CRISPR; Resource (disambiguation); Computer science; Biology; Genetics; Gene; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007211189,0.0004166747,0.0003634876,0.0001026849,0.0004587541,0.0002300663,0.0008734082,0.0006890109,0.0000563433],"category_scores_gemma":[0.0001993531,0.0003046888,0.0004363834,0.00008211229,0.000153588,0.000004217075,0.0001394891,0.001342119,0.00001377261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002800518,"about_ca_system_score_gemma":0.0001190863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003864769,"about_ca_topic_score_gemma":0.00000333123,"domain_scores_codex":[0.9980164,0.000133173,0.0004544874,0.0004175318,0.0003000444,0.0006783387],"domain_scores_gemma":[0.9986408,0.0000769157,0.0002681392,0.0006767982,0.0002437442,0.00009358923],"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":[0.00004348901,0.00001025732,0.00001405748,0.00006662255,0.0001959149,0.00003226286,0.0001223068,0.0001066533,0.02414962,0.000003475465,0.9738054,0.001449997],"study_design_scores_gemma":[0.0004890489,0.0002391908,0.00004847441,0.00008897966,0.0001644805,0.0007128596,0.0001141262,0.00007064579,0.0602049,0.0001557487,0.937319,0.000392517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.02983185,0.02010801,0.2823175,0.6568679,0.005637972,0.001709958,0.0002779374,0.0001173046,0.003131559],"genre_scores_gemma":[0.1406963,0.002793428,0.006131363,0.6648408,0.1588582,0.0001426831,0.001072199,0.0008659787,0.02459908],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2761862,"threshold_uncertainty_score":0.9999405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01856063147560924,"score_gpt":0.3178383942852925,"score_spread":0.2992777628096832,"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."}}