{"id":"W4205961001","doi":"10.1101/2022.01.07.22268899","title":"Mendelian gene identification through mouse embryo viability screening","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; SickKids Foundation; Toronto Centre for Phenogenomics; Hospital for Sick Children","funders":"","keywords":"Biology; Gene; Phenotype; Genetics; Loss function; Lethal allele; Disease; Mendelian inheritance; Genome; Gene knockout; Computational biology; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00112534,0.000610948,0.0004072399,0.002264652,0.0003707462,0.0006745408,0.0006851429,0.0004894279,0.005513749],"category_scores_gemma":[0.0009301149,0.0003200221,0.0003808941,0.0005150185,0.0004421095,0.0002217352,0.0008124509,0.0007024352,0.002683663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002816256,"about_ca_system_score_gemma":0.000299911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007379076,"about_ca_topic_score_gemma":0.001235324,"domain_scores_codex":[0.9993269,0.000113089,0.00004462298,0.0001521857,0.0003040889,0.00005894515],"domain_scores_gemma":[0.9994272,0.0002161919,0.0001153736,0.0001159848,0.0000708387,0.00005447774],"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":[0.0002721972,0.00004094782,0.005836985,0.000139645,0.00005465641,0.0009729004,0.00008919695,0.001040181,0.9542018,0.006384804,0.002275412,0.02869141],"study_design_scores_gemma":[0.00007825637,0.0002707744,0.01975833,0.00006558155,0.00008218524,0.003738065,0.00008609523,0.01710298,0.90682,0.004097308,0.0478529,0.00004758168],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4451621,0.002483315,0.5096754,0.0006553108,0.0001758421,0.0006251922,0.01696956,0.007243582,0.01700967],"genre_scores_gemma":[0.6973706,0.001895119,0.2599265,0.0003491494,0.00005952425,0.0005267211,0.01791117,0.001577768,0.02038338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005513749,"threshold_uncertainty_score":0.01844537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02280909323366441,"score_gpt":0.2784245786817987,"score_spread":0.2556154854481342,"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."}}