{"id":"W4407774429","doi":"10.1007/s00027-025-01172-4","title":"Environmental heterogeneity drives the spatial distribution of macrobenthos in the Yellow River Delta wetland","year":2025,"lang":"en","type":"article","venue":"Aquatic Sciences","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Macrobenthos; Wetland; Delta; Spatial distribution; River delta; Environmental science; Spatial heterogeneity; Distribution (mathematics); Hydrology (agriculture); Geology; Physical geography; Ecology; Oceanography; Geography; Remote sensing; Biomass (ecology); Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008628225,0.00009409063,0.0001045714,0.00002175308,0.0002525092,0.00003999987,0.0006398356,0.0000288614,0.00009398046],"category_scores_gemma":[0.00004911396,0.00005033632,0.00004941737,0.0003552374,0.001022949,0.0001187685,0.0002432509,0.00006843617,0.00004509013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007567229,"about_ca_system_score_gemma":0.00001298196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003715222,"about_ca_topic_score_gemma":0.01499214,"domain_scores_codex":[0.9987767,0.0001582541,0.0002298822,0.0002293877,0.0003976856,0.0002080771],"domain_scores_gemma":[0.999434,0.00022615,0.0000862372,0.0002331895,0.000001041897,0.00001939021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006660818,0.00006878068,0.9893069,0.000005388386,0.000004917831,0.00000136541,0.0008521083,0.001709593,0.0009593487,0.0001405131,0.0001776939,0.006766739],"study_design_scores_gemma":[0.0001650149,0.00005041352,0.924108,0.00002151913,0.00001343358,0.000003537828,0.0008137622,0.07241893,0.0006304487,0.001230986,0.0004690718,0.00007490932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952444,0.00003401484,0.002673335,0.0006107969,0.0001123876,0.000274582,0.00002755877,0.000004716249,0.001018206],"genre_scores_gemma":[0.999755,0.00002176153,0.00006011063,0.00009090156,0.000008465101,0.00001406498,0.000009711448,0.000001736658,0.00003822294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07070933,"threshold_uncertainty_score":0.8365967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007788896250376897,"score_gpt":0.2280696551937196,"score_spread":0.2202807589433426,"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."}}