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Record W2607461018 · doi:10.1080/02757540.2017.1303050

Combined modelled and measured uptakes of arsenic and uranium by <i>Lemna gibba</i> G3 cells

2017· article· en· W2607461018 on OpenAlex
Martin Mkandawire, David J. G. Irwin

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

VenueChemistry and Ecology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsCape Breton University
Fundersnot available
KeywordsLemna gibbaArsenicBiosorptionEnvironmental chemistryMicrocosmChemistryMetalBioaccumulationBiophysicsMetal ions in aqueous solutionMembraneUraniumDepleted uraniumLimitingBiochemistryBiologyEcologyAdsorptionAquatic plant

Abstract

fetched live from OpenAlex

With data from in vitro and in situ investigations, we developed a mathematical model to describe cellular uptake of uranium and arsenic in solution by living Lemna gibba under homeostatic regulation. The model considers the ability of healthy cells to resist accumulation of toxic metal species by regulating physicochemical properties of the cell membrane. In the bulk solution, the ratio of the total amounts of bioavailable metal ions to the metal ions uptake by the cells is very high. Consequently, the main rate-limiting processes of uptake are the biosorption kinetics on both external and internal surfaces at the biological interface, and the transport of the metal ions across the cell membrane. The model prediction correlates well with uptake results from field and microcosm experiments for uranium and arsenic by L. gibba, a model ecotoxicological test organism.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.513

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 science0.0000.000
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 head0.008
GPT teacher head0.200
Teacher spread0.191 · 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