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Record W2157693050 · doi:10.1088/0952-4746/30/2/s06

An international model validation exercise on radionuclide transfer and doses to freshwater biota

2010· article· en· W2157693050 on OpenAlexaffabout
T. Yankovich, S. Vives-Lynch, N.A. Beresford, C.L. Barnett, K. Beaugelin­-Seiller, Justin Brown, J-J Cheng, D. Copplestone, R. Heling, A. Hosseini, B.J. Howard, S. Kamboj, А. И. Крышев, T. Nedveckaitė, J.T. Smith, Michael D. Wood

Bibliographic record

VenueJournal of Radiological Protection · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsNatural Resources Canada
FundersNatural Environment Research Council
KeywordsRadionuclideTrophic levelBiotaEnvironmental scienceInvertebratePerchEcologyEnvironmental chemistryBiologyFish <Actinopterygii>ChemistryFisheryPhysics

Abstract

fetched live from OpenAlex

Under the International Atomic Energy Agency (IAEA)'s EMRAS (Environmental Modelling for Radiation Safety) programme, activity concentrations of (60)Co, (90)Sr, (137)Cs and (3)H in Perch Lake at Atomic Energy of Canada Limited's Chalk River Laboratories site were predicted, in freshwater primary producers, invertebrates, fishes, herpetofauna and mammals using eleven modelling approaches. Comparison of predicted radionuclide concentrations in the different species types with measured values highlighted a number of areas where additional work and understanding is required to improve the predictions of radionuclide transfer. For some species, the differences could be explained by ecological factors such as trophic level or the influence of stable analogues. Model predictions were relatively poor for mammalian species and herpetofauna compared with measured values, partly due to a lack of relevant data. In addition, concentration ratios are sometimes under-predicted when derived from experiments performed under controlled laboratory conditions representative of conditions in other water bodies.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.021
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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 designSimulation or modeling
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

Citations47
Published2010
Admission routes2
Has abstractyes

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