{"id":"W3160049122","doi":"10.22541/au.158809437.78730399","title":"Whole genome sequences from non-invasively collected samples","year":2020,"lang":"en","type":"dataset","venue":"Authorea","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Trent University","funders":"Environment and Climate Change Canada; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada; Government of Alberta; Manitoba Hydro; Compute Canada","keywords":"Genome; Biology; Genomics; Population; Evolutionary biology; DNA sequencing; Threatened species; Computational biology; Genetics; Ecology; DNA; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00007457729,0.0003751447,0.0003707348,0.00005425624,0.0001551721,0.00004882484,0.000768411,0.0008098602,0.0001095008],"category_scores_gemma":[0.0001048399,0.0003602378,0.0001831635,0.0001833397,0.0001821649,0.000001576566,0.0003598527,0.000304172,0.0002701433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002038696,"about_ca_system_score_gemma":0.0002633096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000736572,"about_ca_topic_score_gemma":0.0003507965,"domain_scores_codex":[0.9982824,0.00008491005,0.0003220367,0.0008733398,0.000136565,0.0003007785],"domain_scores_gemma":[0.9986705,0.00002147357,0.0002243527,0.00083678,0.00008734905,0.0001595296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001495945,0.00002530371,0.000007149078,0.00001156009,0.0001020389,0.00001185932,0.000005574434,0.000001219463,0.3163832,0.000005963504,0.6833678,0.0000633721],"study_design_scores_gemma":[0.0001508444,0.0002094724,0.0003476722,0.00001778836,0.0000968589,0.000008179593,0.00001142511,0.000003280315,0.02444741,0.0002330402,0.9740653,0.0004087116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001208695,0.0003953014,0.002430544,0.000481169,0.00008286335,0.0004666789,0.9947533,0.00004131566,0.0001401162],"genre_scores_gemma":[0.001256934,0.0009431198,0.003465444,0.001237363,0.0004835835,0.0002658921,0.9920833,0.0000351789,0.0002291982],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2919358,"threshold_uncertainty_score":0.999885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997653933704498,"score_gpt":0.269466811833326,"score_spread":0.249490272496281,"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."}}