{"id":"W6911063395","doi":"10.5061/dryad.fp1k7","title":"Data from: History matters more when explaining genetic diversity within the context of the core-periphery hypothesis","year":2015,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetic diversity; Range (aeronautics); Context (archaeology); Environmental niche modelling; Population; Species richness; Ecosystem diversity; Population genetics; Diversity (politics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002479531,0.0008540591,0.001056283,0.002117174,0.0007003439,0.002132949,0.00179182,0.001393635,0.02691819],"category_scores_gemma":[0.01760763,0.0005031375,0.0006581418,0.005409019,0.0005231141,0.002238452,0.001936615,0.001733634,0.01270829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191911,"about_ca_system_score_gemma":0.001257621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0266507,"about_ca_topic_score_gemma":0.04655943,"domain_scores_codex":[0.9985915,0.0003513289,0.0002336316,0.0003903797,0.0002661059,0.0001670422],"domain_scores_gemma":[0.9956769,0.001916107,0.0006763622,0.001050151,0.0004929719,0.0001875045],"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":[0.0003256566,0.00007147124,0.07853516,0.003621786,0.0003865955,0.0002313333,0.0007427515,0.003064471,0.000871493,0.009455625,0.8815882,0.02110548],"study_design_scores_gemma":[0.0003137494,0.00001916563,0.06433332,0.0008066653,0.0001011875,0.0001548526,0.0005166783,0.001513306,0.0005724842,0.009702406,0.9218957,0.00007055164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003452029,0.0002862717,0.0007146869,0.0006557392,0.00006030672,0.00001911647,0.9918531,0.0002655675,0.002693216],"genre_scores_gemma":[0.01884224,0.0002620362,0.00374276,0.0003892418,0.00003169966,0.0002104701,0.9750635,0.0003160826,0.001142042],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02691819,"threshold_uncertainty_score":0.09005028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09675292022370066,"score_gpt":0.2553217997759681,"score_spread":0.1585688795522674,"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."}}