{"id":"W2930808060","doi":"10.1038/s41597-019-0024-7","title":"Geo-referenced population-specific microsatellite data across American continents, the MacroPopGen Database","year":2019,"lang":"en","type":"article","venue":"Scientific Data","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; Golder Associates (Canada); BGC Engineering (Canada); Concordia University","funders":"Concordia University; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Fish migration; Microsatellite; Biodiversity; Genetic diversity; Population; Ecology; Intraspecific competition; Zoology; Allele; Demography; Genetics","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":[0.0008022444,0.0001696641,0.0001493981,0.00003054705,0.0004460312,0.0004627689,0.003825568,0.0000634282,0.0003280598],"category_scores_gemma":[0.0000620583,0.0001313067,0.00003339089,0.000308073,0.0003843756,0.00004119337,0.004258111,0.0001202724,0.000405379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006987927,"about_ca_system_score_gemma":0.00004664205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000356699,"about_ca_topic_score_gemma":0.000520827,"domain_scores_codex":[0.9977065,0.00008823336,0.0002444933,0.001254939,0.0003431015,0.0003626735],"domain_scores_gemma":[0.9928875,0.00001544361,0.0001741291,0.006736237,0.00009629047,0.00009038964],"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":[0.0001571218,0.00008350872,0.1399624,0.00003620497,0.0001297888,0.000003656518,0.0002978812,0.00008590946,0.300859,0.000240968,0.5165897,0.04155387],"study_design_scores_gemma":[0.0003137455,0.00001693636,0.07973605,0.000007696442,0.00001539634,0.00000604688,0.0003566452,0.0002085961,0.00269334,0.00002959776,0.9164139,0.0002020246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550625,0.0005917915,0.000365865,0.0003045053,0.00165083,0.0003350987,0.04141769,0.00001706419,0.0002546723],"genre_scores_gemma":[0.7803586,0.0001091683,0.001371628,0.0001912395,0.0001445286,0.000001262297,0.212252,0.00001300083,0.005558687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3998242,"threshold_uncertainty_score":0.7108921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05393613729136078,"score_gpt":0.3173182112775451,"score_spread":0.2633820739861844,"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."}}