{"id":"W3149134227","doi":"10.1101/2021.03.31.437877","title":"Predicting skeletal stature using ancient DNA","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institutes of Health; Deutsche Forschungsgemeinschaft; National Institute of General Medical Sciences; Charles E. Kaufman Foundation; Alfred P. Sloan Foundation","keywords":"Genetic variation; Biology; Explained variation; Evolutionary biology; Demography; Statistics; Genetics; Mathematics","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":[0.000948963,0.0003661442,0.0002929689,0.001590578,0.0001946022,0.0005570445,0.0002967881,0.0002745154,0.001819817],"category_scores_gemma":[0.002663278,0.0001572766,0.0002813814,0.001372688,0.0003357745,0.0003676901,0.0005050438,0.0002856538,0.0004044986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001712185,"about_ca_system_score_gemma":0.0001603029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003689343,"about_ca_topic_score_gemma":0.005792042,"domain_scores_codex":[0.9996433,0.000141213,0.00001998636,0.0001232983,0.00004660349,0.00002557453],"domain_scores_gemma":[0.9986853,0.0006997449,0.0002914762,0.000083815,0.0001270282,0.0001127049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004809294,0.00001424738,0.9739758,0.00001662214,0.0001135441,0.00006681746,0.00006216507,0.008342757,0.002290273,0.000231688,0.00008779463,0.01475026],"study_design_scores_gemma":[0.000008570067,0.00005928982,0.9204154,0.00002226042,0.00003683471,0.0001553452,0.0001347991,0.07666808,0.0007821336,0.001444538,0.0002582676,0.00001442934],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931914,0.00007180686,0.005889059,0.0000221776,0.000002639327,0.000002980004,0.0003772694,0.00001977849,0.0004228809],"genre_scores_gemma":[0.9976522,0.00002779343,0.001754917,0.000004432764,0.000002963156,0.000001962616,0.0003886732,0.000003542489,0.0001635618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003689343,"threshold_uncertainty_score":0.007335722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393572004776364,"score_gpt":0.2492788139542163,"score_spread":0.2353430939064527,"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."}}