{"id":"W4391477679","doi":"10.20944/preprints202402.0027.v1","title":"CRISPR-Cas Associated Cells and Animal Mediated Biomedical Modelling","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amgen (Canada); York University","funders":"","keywords":"CRISPR; Computational biology; Biology; Animal model; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008792644,0.0004883019,0.0005369828,0.0002209272,0.000071446,0.00006459242,0.0005435303,0.00109895,0.0001747151],"category_scores_gemma":[0.0002889211,0.0005068377,0.0003236268,0.0001843356,0.0002299165,0.000003887927,0.004910314,0.001068442,0.0002873419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007995756,"about_ca_system_score_gemma":0.0001902258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002533324,"about_ca_topic_score_gemma":0.00002652083,"domain_scores_codex":[0.9968013,0.0001701577,0.0006133373,0.001597058,0.0003765053,0.0004416259],"domain_scores_gemma":[0.9981936,0.00003732557,0.0002459867,0.001090811,0.0001953691,0.0002368702],"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":[0.00004774472,0.0001723772,0.007378097,0.0001793836,0.0006661782,0.00006039663,0.0001611258,0.000162337,0.9889807,0.00001085683,0.002043104,0.0001377371],"study_design_scores_gemma":[0.0002395525,0.00007389409,0.001773971,0.0001638641,0.0003940683,0.000009615051,0.00003601388,0.01228495,0.9734518,0.001062248,0.009843534,0.0006664963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921992,0.001324774,0.002830313,0.0002670013,0.0001428716,0.0004012609,0.00007496254,0.0002419235,0.002517658],"genre_scores_gemma":[0.9945276,0.002106711,0.0006086653,0.0001556926,0.0002674679,0.00008899839,0.0009234193,0.00009755993,0.00122392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01552887,"threshold_uncertainty_score":0.9997383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05019346237447112,"score_gpt":0.3375086740545153,"score_spread":0.2873152116800442,"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."}}