{"id":"W4411161199","doi":"10.1111/geb.70074","title":"Arctic Migrations Shape Global Meta‐Communities: Contrasting Insights From Species Occurrence, Abundance and Biomass","year":2025,"lang":"en","type":"article","venue":"Global Ecology and Biogeography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Sherbrooke; Université du Québec à Rimouski","funders":"Fonds de recherche du Québec – Nature et technologies; Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Nunavut Wildlife Management Board; Environment and Climate Change Canada; Natural Resources Canada; Indigenous and Northern Affairs Canada; Government of Canada; Canada First Research Excellence Fund; Canada Research Chairs; Université Laval; Polar Knowledge Canada; ArcticNet; Parks Canada; Garfield Weston Foundation; Université du Québec à Rimouski","keywords":"Abundance (ecology); Biomass (ecology); Ecology; Temperate climate; Arctic; Community structure; Relative species abundance; Geography; Taxon; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004063761,0.0001949936,0.0002374004,0.001409419,0.0004071585,0.0008951093,0.0001351084,0.0002053481,0.001154746],"category_scores_gemma":[0.001380688,0.0001489295,0.0002402905,0.001224092,0.0004344232,0.0005483946,0.0005747977,0.0001847102,0.0001112452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004579526,"about_ca_system_score_gemma":0.000271157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01453477,"about_ca_topic_score_gemma":0.03549409,"domain_scores_codex":[0.9998407,0.00005103536,0.000009630969,0.00004701019,0.00002420159,0.00002735229],"domain_scores_gemma":[0.9989924,0.0002827565,0.0003355083,0.00007277068,0.0001900732,0.0001265267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001350743,0.00003139878,0.9724334,0.00007924592,0.0002209836,0.00008199117,0.001771058,0.003409545,0.009115015,0.000701306,0.0002051245,0.01181594],"study_design_scores_gemma":[0.000002186435,0.00002423016,0.9920093,0.00001669648,0.00003288935,0.00003882256,0.001561946,0.0052875,0.0002121692,0.0004753578,0.000331868,0.000007062714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985484,0.00007950005,0.0006326955,0.00001816477,0.000001173041,0.000002589849,0.0001874075,0.000005975329,0.0005240353],"genre_scores_gemma":[0.9991515,0.00005328425,0.000535645,0.000005632092,0.00000173218,0.00000317223,0.0001726896,0.00000213353,0.00007422973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01453477,"threshold_uncertainty_score":0.02890033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982035978069079,"score_gpt":0.2433241499728832,"score_spread":0.2235037901921924,"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."}}