{"id":"W3217632346","doi":"10.1038/s41559-021-01609-7","title":"Integrate geographic scales in equity, diversity and inclusion","year":2021,"lang":"en","type":"letter","venue":"Nature Ecology & Evolution","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Equity (law); Diversity (politics); Inclusion (mineral); Geography; Data science; Ecology; Evolutionary biology; Biology; Computer science; Sociology; Anthropology; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01663033,0.0004646874,0.001821092,0.0009628159,0.008912537,0.009556582,0.002104708,0.06290534,0.007948354],"category_scores_gemma":[0.07157358,0.0006556432,0.0009224451,0.001309086,0.02319958,0.01275874,0.00701166,0.05277779,0.003373429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008371831,"about_ca_system_score_gemma":0.009361018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02607586,"about_ca_topic_score_gemma":0.05306185,"domain_scores_codex":[0.9903603,0.003281242,0.0009267769,0.001471379,0.002480573,0.001479756],"domain_scores_gemma":[0.9420413,0.04445936,0.001547091,0.001857801,0.005905595,0.004188939],"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":[0.00008284607,0.000042918,0.002829294,0.00006714898,0.00002709586,0.0006291094,0.001807588,0.0001025551,0.00009527333,0.1198763,0.8499622,0.02447771],"study_design_scores_gemma":[0.0001826356,0.00006010192,0.005754211,0.0006487424,0.00005200202,0.0009397353,0.006412042,0.001055127,0.0003323281,0.3982396,0.5861652,0.0001582649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005863177,0.0005252298,0.0001506757,0.9914932,0.003607019,0.000004457361,0.00002720528,0.000005721815,0.003600345],"genre_scores_gemma":[0.0235195,0.0005472302,0.0003760123,0.9484062,0.02072521,0.00006135013,0.0000209048,0.00002275645,0.00632085],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06290534,"threshold_uncertainty_score":0.08795071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084056415622106,"score_gpt":0.2857715433670137,"score_spread":0.2749309792107927,"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."}}