{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005357285,0.0005064002,0.0004226592,0.0001197165,0.0001990416,0.0002530061,0.0005252151,0.0008337288,0.00004667813],"category_scores_gemma":[0.0002952612,0.0005445229,0.0002509667,0.0002864953,0.0002092301,0.00000751181,0.001312649,0.0007629832,0.00001090691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139409,"about_ca_system_score_gemma":0.001410551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006956983,"about_ca_topic_score_gemma":0.00001107368,"domain_scores_codex":[0.9967679,0.0001713236,0.0004354006,0.001295868,0.0005426116,0.0007868434],"domain_scores_gemma":[0.9972742,0.00001374226,0.0002476683,0.001449952,0.0006795637,0.0003349035],"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":[0.00001820213,0.00007458642,0.008316183,0.0002190843,0.0001816834,0.00004770432,0.000007293871,0.0006565735,0.9899795,0.00001988454,0.0004764582,0.000002855275],"study_design_scores_gemma":[0.0004639976,0.0001186548,0.0554327,0.0002721037,0.00008724658,1.425262e-7,0.00001837728,0.002115518,0.9334021,3.032106e-7,0.007295415,0.0007934142],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919236,0.003722422,0.002461902,0.00004979271,0.001125391,0.0004507562,0.0001866948,0.00006186533,0.00001760598],"genre_scores_gemma":[0.9890287,0.0003809134,0.00911946,0.0001721594,0.001096319,0.00005155379,0.000005322167,0.0001253595,0.00002021785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05657736,"threshold_uncertainty_score":0.9997006,"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."}}