{"id":"W4388765308","doi":"10.1101/2023.11.15.567075","title":"Genetically encoded affinity reagents (GEARs): A toolkit for visualizing and manipulating endogenous protein function <i>in vivo</i>","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Surdna Foundation; Yale University","keywords":"Genome editing; Computational biology; CRISPR; Biology; Cas9; Function (biology); Epitope; Gene; Cell biology; Genetics; Antibody","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000798389,0.001008737,0.0005470585,0.0009948214,0.0004110425,0.0009421666,0.001237669,0.001004981,0.003744273],"category_scores_gemma":[0.000837809,0.000776418,0.0006034272,0.0004243782,0.0006921224,0.0008572335,0.001677247,0.001829138,0.003601618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004603603,"about_ca_system_score_gemma":0.0006137652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006399201,"about_ca_topic_score_gemma":0.001238317,"domain_scores_codex":[0.9991105,0.0001086106,0.00006351277,0.000141101,0.0004915069,0.00008471943],"domain_scores_gemma":[0.9995137,0.0001131765,0.0001253661,0.0001163207,0.00006259713,0.00006885119],"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":[0.00003812222,0.00001839484,0.0002966748,0.0002546117,0.00002621954,0.0001084936,0.00005267856,0.0003046074,0.9697271,0.002542041,0.003575514,0.02305544],"study_design_scores_gemma":[0.00001335175,0.00004482996,0.0005039606,0.00002640391,0.00002279737,0.0007429547,0.00001619926,0.001812429,0.9371569,0.0005508312,0.05907768,0.00003164354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07535344,0.005024398,0.8809937,0.0008608091,0.0004271815,0.000319196,0.003009839,0.02206279,0.01194865],"genre_scores_gemma":[0.2639367,0.007397359,0.6925284,0.0008544787,0.0001046853,0.0008414825,0.005676196,0.003725279,0.02493537],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003744273,"threshold_uncertainty_score":0.01252586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02897452212729375,"score_gpt":0.2685936088277978,"score_spread":0.239619086700504,"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."}}