{"id":"W4225160828","doi":"10.2478/ebtj-2022-0008","title":"Genetically modified mice for research on human diseases: A triumph for Biotechnology or a work in progress?","year":2022,"lang":"en","type":"article","venue":"The EuroBiotech Journal","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Disease; Genetically engineered; Biology; Human disease; Gene; Gene knockout; Computational biology; Gene knockin; Animal model; Genetically modified organism; Genetics; Epigenetics; Gene targeting; Genetic model; Drug discovery; Neuroscience; Bioinformatics; Medicine; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.002798169,0.0001892983,0.0002168178,0.0003839356,0.001148193,0.00009768907,0.001421117,0.0001979517,0.00003511781],"category_scores_gemma":[0.0004375163,0.0001346391,0.0001814911,0.0006409946,0.0003539903,0.000003471455,0.0006509246,0.001116952,0.000004731794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303354,"about_ca_system_score_gemma":0.0003163184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002637224,"about_ca_topic_score_gemma":0.000007417234,"domain_scores_codex":[0.9970559,0.0006923548,0.0003578043,0.0005118444,0.0004798874,0.0009021595],"domain_scores_gemma":[0.9987786,0.0002252797,0.0001205922,0.0005584945,0.0001779705,0.0001390483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01586875,0.001011471,0.00007892927,0.00008204228,0.0001478718,0.00009407336,0.0001034651,0.001874566,0.9359357,0.001005899,0.03399577,0.009801508],"study_design_scores_gemma":[0.01567027,0.0236361,0.001471078,0.0001776189,0.00009845813,0.0009021197,0.001124415,0.001801665,0.4663354,0.004923663,0.4827274,0.001131801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725999,0.001646136,0.003521981,0.01822509,0.0002514928,0.003394555,0.0001955114,0.00003344612,0.0001318344],"genre_scores_gemma":[0.9945265,0.0001947815,0.001108144,0.0002718191,0.0003968029,0.0009497954,0.00006093642,0.00007364745,0.002417587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4696003,"threshold_uncertainty_score":0.883109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1053948379692874,"score_gpt":0.3996939807411718,"score_spread":0.2942991427718843,"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."}}