{"id":"W2588631423","doi":"10.1093/bioinformatics/btx102","title":"<i>GARLIC</i>: Genomic Autozygosity Regions Likelihood-based Inference and Classification","year":2017,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Inference; Computer science; Artificial intelligence","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":[0.0002697813,0.0001102548,0.0001260442,0.00002739458,0.0004341359,0.00007687078,0.0002387724,0.0001726397,0.000004296212],"category_scores_gemma":[0.0004378207,0.0001040251,0.00004583142,0.00001720124,0.0001447077,0.000008769924,0.0001293645,0.00006857161,0.00003062208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001496991,"about_ca_system_score_gemma":0.0001116614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002608928,"about_ca_topic_score_gemma":0.00006381114,"domain_scores_codex":[0.9993147,0.00002724895,0.0002497603,0.000140385,0.00006170337,0.0002062114],"domain_scores_gemma":[0.9988892,0.00002326483,0.0003121647,0.000612648,0.00007515641,0.00008754438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005854431,0.0001531322,0.8452223,0.0001421113,0.0001422841,0.000001216802,0.0004204868,0.0002331243,0.07214905,0.003697919,0.02675394,0.05102592],"study_design_scores_gemma":[0.0004664749,0.0001156586,0.9393879,0.00001087282,0.00002471074,0.000004170301,0.00007636596,0.0320494,0.0008391202,0.0004395184,0.02637919,0.0002066699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438577,0.0001142817,0.04766384,0.001527318,0.000161634,0.0002096029,0.00003707282,0.00002256045,0.006406032],"genre_scores_gemma":[0.9814329,0.0002152823,0.01743129,0.0005361426,0.0000740824,0.00001431737,0.0001048481,0.000007776707,0.0001834068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09416557,"threshold_uncertainty_score":0.4242021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03143508679184543,"score_gpt":0.28629253257251,"score_spread":0.2548574457806646,"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."}}