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Record W2024212563 · doi:10.3109/17435391003628713

An ecotoxicological characterization of nanocrystalline cellulose (NCC)

2010· article· en· W2024212563 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNanotoxicology · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of OttawaEnvironment and Climate Change CanadaOntario GenomicsFPInnovations
FundersFPInnovationsU.S. Environmental Protection Agency
KeywordsGenotoxicityToxicityCelluloseEcotoxicityEnvironmental chemistryBiologyToxicologyChemistryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The pulp and paper industry in Canada is developing technology for the production and use of nanocrystalline cellulose (NCC). A key component of the developmental work is an assessment of potential environmental risks. Towards this goal, NCC samples as well as carboxyl methyl cellulose (CMC), a surrogate of the parent cellulosic material, were subjected to an ecotoxicological evaluation. This involved toxicity tests with rainbow trout hepatocytes and nine aquatic species. The hepatocytes were most sensitive (EC20s between 10 and 200 mg/l) to NCC, although neither NCC nor CMC caused genotoxicity. In tests with the nine species, NCC affected the reproduction of the fathead minnow at (IC25) 0.29 g/l, but no other effects on endpoints such as survival and growth occurred in the other species at concentrations below 1 g/l, which was comparable to CMC. Based on this ecotoxicological characterization, NCC was found to have low toxicity potential and environmental risk.

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 categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.262
Teacher spread0.250 · 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