{"id":"W4403990713","doi":"10.5376/gab.2024.15.0028","title":"Harnessing Gene Editing Tools to Study ASFV Pathogenesis","year":2024,"lang":"en","type":"article","venue":"Genomics and Applied Biology","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genome editing; Pathogenesis; Biology; Genetics; Gene; Computational biology; Computer science; CRISPR; Immunology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003654688,0.0001393154,0.0002056228,0.00001944286,0.000201435,0.0001079574,0.0001362962,0.00007542191,0.0001030709],"category_scores_gemma":[0.00001745863,0.00005800024,0.00004388464,0.0001543795,0.00003541275,0.00002577453,0.0002361984,0.00006467177,0.00007884481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001362735,"about_ca_system_score_gemma":0.000003606181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002892496,"about_ca_topic_score_gemma":0.00003528811,"domain_scores_codex":[0.9989522,0.00004784645,0.0002016086,0.0004689887,0.00003235381,0.0002970718],"domain_scores_gemma":[0.9996806,0.000138392,0.00002949205,0.00004165625,0.000009847984,0.00009999012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002215428,0.00003214575,0.005091609,0.000005136411,0.00003323318,0.000006537823,0.00009806688,0.000004734794,0.5235223,0.004012806,0.0002214152,0.4669498],"study_design_scores_gemma":[0.000320089,0.0009870338,0.783034,0.00001508776,0.000157764,0.00001110177,0.004035573,0.0004741212,0.00256873,0.0100496,0.1975104,0.000836521],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967963,0.0005036691,0.000113077,0.001018092,0.0001803756,0.0003228456,0.00005377835,0.00008269374,0.0009291431],"genre_scores_gemma":[0.997726,0.00006524244,0.000360753,0.0008899146,0.0007807534,0.00005537681,0.00007893908,0.000001761693,0.0000412853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7779424,"threshold_uncertainty_score":0.2365181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04502149973250745,"score_gpt":0.2587688207525618,"score_spread":0.2137473210200543,"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."}}