{"id":"W4393866027","doi":"10.1002/ecy.4280","title":"Environmental heterogeneity at two spatial scales affects litter diversity–decomposition relationships","year":2024,"lang":"en","type":"article","venue":"Ecology","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"U.S. Department of Veterans Affairs","keywords":"Biodiversity; Ecology; Spatial ecology; Ecosystem; Habitat; Complementarity (molecular biology); Spatial heterogeneity; Environmental science; Microcosm; Environmental change; Beta diversity; Plant litter; Geography; Biology; Climate change","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":[0.0003809941,0.0003027358,0.0004576628,0.0004813915,0.0002533179,0.0006762033,0.000257063,0.0002787256,0.0006423313],"category_scores_gemma":[0.0009875204,0.0002242538,0.0003402108,0.0002663582,0.0004985908,0.0003768097,0.0009732613,0.000316794,0.00005967511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003171705,"about_ca_system_score_gemma":0.0001562676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001640298,"about_ca_topic_score_gemma":0.00362545,"domain_scores_codex":[0.999651,0.00008997376,0.00003319984,0.0001250306,0.00004237711,0.00005832635],"domain_scores_gemma":[0.9989236,0.000454329,0.0003107736,0.00008799978,0.00007304642,0.0001502341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007399587,0.0001595652,0.7367644,0.0001389237,0.0002921614,0.0002153579,0.0002631034,0.005346699,0.247603,0.0003537325,0.00005736832,0.008065721],"study_design_scores_gemma":[0.000007426604,0.0001325868,0.9916742,0.000004299874,0.00004554864,0.00008077568,0.00009119642,0.004339399,0.003347563,0.0001941829,0.00007447795,0.000008365267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992411,0.00007050359,0.0004989248,0.000005771094,6.589498e-7,0.000003277754,0.00003528588,0.000005733581,0.000138615],"genre_scores_gemma":[0.9996055,0.00001547263,0.0003005405,0.000005760801,8.244601e-7,0.000003390747,0.00003534968,0.000001667388,0.00003148801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001640298,"threshold_uncertainty_score":0.003261566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168215496325529,"score_gpt":0.2260605055429723,"score_spread":0.214378350579717,"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."}}