{"id":"W4412539639","doi":"10.1007/s10201-025-00807-7","title":"Effects of environmental stressors on macroinvertebrates trait distribution in the sediments of a southern Nigerian river","year":2025,"lang":"en","type":"article","venue":"Limnology","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Invertebrate; Stressor; Environmental science; Trait; Distribution (mathematics); Geology; Ecology; Geochemistry; Biology; Neuroscience; Mathematics; Computer 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":[0.0001561441,0.0002243409,0.0002685988,0.0004022493,0.001013519,0.0006199305,0.0001298523,0.0002853402,0.000554598],"category_scores_gemma":[0.0004558737,0.000206222,0.0001181566,0.0005830209,0.000600855,0.0003039084,0.0005940291,0.0002240614,0.00007884434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005426614,"about_ca_system_score_gemma":0.000563642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01769583,"about_ca_topic_score_gemma":0.06372806,"domain_scores_codex":[0.9998782,0.00002850593,0.0000155014,0.00002652947,0.0000155505,0.0000358117],"domain_scores_gemma":[0.9997358,0.00005015197,0.0000872499,0.000008215522,0.00005637501,0.00006219398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002947553,0.000122791,0.9821512,0.00004694855,0.000051327,0.0008869712,0.003393024,0.0002369067,0.009188022,0.0001080297,0.00005805095,0.003462058],"study_design_scores_gemma":[0.000001083626,0.0000680024,0.9965392,0.000005661808,0.000008992695,0.00008691612,0.002943703,0.00006382906,0.0001577407,0.00002647149,0.00009582763,0.00000250198],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998584,0.00001554431,0.000007090992,0.000005528108,6.882523e-7,5.791842e-7,0.00001099007,1.910435e-7,0.0001010043],"genre_scores_gemma":[0.9998111,0.00002885129,0.00001540377,0.000004642231,6.846076e-7,0.000001373925,0.00002100243,2.110924e-7,0.000116799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01769583,"threshold_uncertainty_score":0.03518569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002850117814663442,"score_gpt":0.1728549587023486,"score_spread":0.1700048408876852,"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."}}