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Record W2791583331 · doi:10.1016/j.envsoft.2018.01.013

Modelling marine trophic transfer of radiocarbon (14C) from a nuclear facility

2018· article· en· W2791583331 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.

Bibliographic record

VenueEnvironmental Modelling & Software · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of British Columbia
FundersNatural Environment Research CouncilSight Research UK
KeywordsTrophic levelEnvironmental scienceMarine ecosystemMicroplasticsFishingEcosystemOceanographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Sellafield marine discharges of 14C are the largest contributor to the global collective dose from the nuclear fuel industry. As such, it is important to understand the fate of these discharges beyond the limitations and scope of empirical analytical investigations for this highly mobile radioactive contaminant. Ecopath with Ecosim (EwE) is widely used to model anthropogenic impacts on ecosystems, such as fishing, although very few EwE studies have modelled the fate of bioavailable contaminants. This work presents, for the first time, a spatial-temporal 14C model utilising recent developments in EwE software to predict the ecological fate of anthropogenic 14C in the marine environment. The model predicted observed trends in 14C activities between different species and through time. It also provided evidence for the integration of Sellafield 14C in species at higher trophic levels through time.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.012
GPT teacher head0.183
Teacher spread0.171 · 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