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Record W2093416166 · doi:10.1093/biosci/biv009

Geographically Isolated Wetlands are Important Biogeochemical Reactors on the Landscape

2015· article· en· W2093416166 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioScience · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsWestern University
FundersGlobal Institute for Water Security, University of Saskatchewan
KeywordsBiogeochemical cycleWetlandEcosystemEcosystem servicesEnvironmental scienceWater qualityAquatic ecosystemBiogeochemistryLandscape ecologyBiological integrityClean Water ActEcologyHydrology (agriculture)HabitatBiologyGeology

Abstract

fetched live from OpenAlex

Wetlands provide many ecosystem services, including sediment and carbon retention, nutrient transformation, and water quality improvement. Although all wetlands are biogeochemical hotspots, geographically isolated wetlands (GIWs) receive fewer legal protections compared with other types of wetlands because of their apparent isolation from jurisdictional waters. Here, we consider controls on biogeochemical functions that influence water quality, and estimate changes in ecosystem service delivery that would occur if these landscape features were lost following recent US Supreme Court decisions (i.e., Rapanos, SWANCC). We conclude that, despite their lack of persistent surfacewater connectivity or adjacency to jurisdictional waters, GIWs are integral to biogeochemical processing on the landscape and therefore maintaining the integrity of US waters. Given the likelihood that any GIW contributes to downstream water quality, we suggest that the burden of proof could be shifted to assuming that all GIWs are critical for protecting aquatic systems until proven otherwise.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.204
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it