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Record W6901857865 · doi:10.6084/m9.figshare.13026457

Invertebrate communities, sediment parameters and food availability of intertidal soft-sediment ecosystems on the north coast of British Columbia, Canada

2020· article· en· W6901857865 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIntertidal zoneEstuaryBenthic zoneInvertebrateSediment

Abstract

fetched live from OpenAlex

The Skeena River estuary supports commercial and culturally important salmon fisheries. However, considerable development has occurred in the area, and more has been proposed. If anthropogenic development degrades this critical habitat, the Skeena salmon run, that every year contributes $110 million to local economies, may be negatively impacted. Benthic invertebrates are common indicator species, as they often respond to disturbances before commercial species, warning of potential impacts. Unfortunately, invertebrates in the Skeena estuary have not been extensively studied, and we lack the detailed understanding of their community structure and dynamics for them to serve as indicator species in this region. Therefore, present conditions of the Skeena estuary are established here (invertebrate community, sediment conditions and food availability), in order to provide the data required both to anticipate changes associated with potential anthropogenic disturbances and to detect changes in this system if development occurs.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.182
Teacher spread0.157 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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