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Record W2912436212 · doi:10.1086/701674

Enhancing bioassessment approaches: development of a river services assessment framework

2019· article· en· W2912436212 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

VenueFreshwater Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsWilfrid Laurier UniversityEnvironment and Climate Change CanadaUniversity of SaskatchewanUniversity of New BrunswickWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEcosystem servicesEcosystem healthEnvironmental resource managementWatershedEcological healthEnvironmental scienceEcosystemEcosystem managementRiver ecosystemWatershed managementConceptualizationEnvironmental planningEcologyComputer science

Abstract

fetched live from OpenAlex

There has been a trend toward increasing anthropocentrism in definitions of river health through the explicit inclusion of societal valuation of ecosystem services provided by rivers. New frameworks and associated indicators of river health are therefore required to centralize ecosystem services within river assessment and management activities. Here, we adopt an anthropocentric conceptualization of rivers to focus on a river’s ability to maintain ecological function and structure that support ecosystem services valued by society. We apply this approach to further existing conceptual models of river assessment by identifying how benthic indicators can be linked to valued ecosystem services in a river services assessment framework. This approach extends bioassessment from a focus on assessing departure from reference condition to also include the evaluation of rivers based on their delivery of ecosystem services. Indicators based on benthic processes and assemblages are widely used in river health assessments; thus, these are reviewed to identify those indicators most closely linked with the provision of river ecosystem services. Finally, we illustrate how our approach can be applied to management through contrasting watershed examples, including a highly modified agricultural region and relatively pristine Arctic watersheds. The proposed approach supports an explicit connection between valued ecosystem services and benthic indicators, providing more targeted assessment results for use in river management decision-making.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.240
Teacher spread0.226 · 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