{"id":"W2892164437","doi":"10.1002/ecs2.2423","title":"Relations of interannual differences in stream litter breakdown with discharge: bioassessment implications","year":2018,"lang":"en","type":"article","venue":"Ecosphere","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Guelph; Canadian Forest Service; University of British Columbia","funders":"Canadian Forest Service; Natural Resources Canada; Simpson Fund; U.S. Forest Service; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Killam Trusts","keywords":"Environmental science; Ecosystem; STREAMS; Ecology; Temperate climate; Atmospheric sciences; Decomposer; Plant litter; Litter; Hydrology (agriculture); Fragmentation (computing); Range (aeronautics); Physical geography; Biology; Geography; Geology","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":[0.001124052,0.0002031459,0.0002160522,0.0007985188,0.0003715671,0.0008052533,0.0003382379,0.0002731312,0.0005879928],"category_scores_gemma":[0.002229809,0.0001392064,0.000211471,0.001046038,0.0002562565,0.0003224291,0.0003549107,0.0002725311,0.0000764603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239665,"about_ca_system_score_gemma":0.000745023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1398391,"about_ca_topic_score_gemma":0.2272771,"domain_scores_codex":[0.9996297,0.00008930975,0.00003593259,0.0001002609,0.00009359929,0.00005120197],"domain_scores_gemma":[0.9981015,0.0006146219,0.0005861497,0.0001023033,0.0004181512,0.0001773294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002634837,0.00001137847,0.9965324,0.00000593044,0.00003195194,0.000007990331,0.00006306484,0.0002476971,0.0009472691,0.0000106492,0.00003877502,0.002076455],"study_design_scores_gemma":[5.71258e-7,0.000006444095,0.9988016,0.00000178072,0.000005905826,0.000008760158,0.00005760659,0.0009344378,0.000119305,0.00001633283,0.0000457057,0.000001544689],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982306,0.0001665553,0.0007743844,0.00003331196,0.000003111844,0.000006440989,0.0004304477,0.00002148945,0.0003337],"genre_scores_gemma":[0.9992613,0.00004326931,0.0003253968,0.00001367196,0.000002984873,0.000004249276,0.0002332049,0.000003205699,0.0001127028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1398391,"threshold_uncertainty_score":0.2780504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008516588996171819,"score_gpt":0.2054211914162951,"score_spread":0.1969046024201233,"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."}}