{"id":"W2946254662","doi":"10.1093/gbe/evz100","title":"PopNetD3—A Network-Based Web Resource for Exploring Population Structure","year":2019,"lang":"en","type":"letter","venue":"Genome Biology and Evolution","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Biology; Population structure; Resource (disambiguation); Population; Data science; Evolutionary biology; Computational biology; Computer science; Demography; Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004450623,0.0001660936,0.000298477,0.00006974741,0.0007714943,0.00003001188,0.0001357663,0.001104564,0.00005797736],"category_scores_gemma":[0.00009722324,0.0001578291,0.00007886664,0.00009472248,0.000111297,0.0000761174,0.00002468016,0.0004451146,0.000005431151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002697461,"about_ca_system_score_gemma":0.0001925439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001452152,"about_ca_topic_score_gemma":0.001253912,"domain_scores_codex":[0.9983691,0.0002764821,0.0002348414,0.0003450777,0.00009857694,0.0006759475],"domain_scores_gemma":[0.9992875,0.00030295,0.000159702,0.0001522668,0.00004619819,0.00005142646],"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":[0.00009548839,0.00000609912,0.2773914,0.0007617826,0.00005485875,0.000002160115,0.0005921738,0.0004687351,0.00001413766,0.02088386,0.698073,0.001656253],"study_design_scores_gemma":[0.0001853432,0.0000398932,0.08168803,0.00003152169,0.00002294493,3.615213e-7,0.0000679318,0.00007606638,7.498906e-8,0.004422344,0.9132881,0.0001773611],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1053622,0.007551187,0.001367528,0.8746592,0.006779809,0.002227836,0.0008133446,0.0002281673,0.001010657],"genre_scores_gemma":[0.5275728,0.0003049054,0.0005536937,0.4390713,0.02591341,0.0001298183,0.004598886,0.00004406966,0.001811095],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.4355879,"threshold_uncertainty_score":0.8519412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04700423048347538,"score_gpt":0.3046440964437923,"score_spread":0.257639865960317,"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."}}