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Record W1947649118 · doi:10.21083/surg.v4i2.1322

Acute toxicity of silver nitrate to in vitro fertilization of the sand dollar, Echinarachnius parma

2011· article· en· W1947649118 on OpenAlexaffvenue
Olivia M. Knight

Bibliographic record

VenueSURG Journal · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSilver nitrateHuman fertilizationSilver nanoparticleNitrateToxicityEnvironmental chemistryToxicologyInvertebrateChemistryBiologyEcologyNanoparticleNanotechnologyMaterials scienceNuclear chemistryAgronomy

Abstract

fetched live from OpenAlex

Considered one of the most toxic heavy metals, interest in silver (both ionic and bound forms) has increased over the past few years due to the production of consumer goods containing Ag⁺-releasing nanoparticles. Investigation into acceptable environmental limits has generated a substantial amount of evidence that even at very low concentrations, silver exposure is detrimental to organism health. This study employed the echinoderm fertilization assay to evaluate acute silver toxicity to a marine invertebrate, Echinarachnius parma. Gametes were procured from E. parma and fertilization success under control conditions was compared to that at varying treatment concentrations of silver nitrate. Exposure to silver nitrate significantly decreased percent fertilization in all treatment concentrations. Remarkably, at concentrations as low as 10⁻⁹ M AgNO₃ percent fertilization decreased by 20-30% compared to the control. The results of this study are consistent with the existing literature, adding to the expanding collection of data that emphasizes the need for more stringent environmental silver regulation criteria in order to ensure the protection of aquatic ecosystems.

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 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 score0.006
Threshold uncertainty score0.999

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)0.0020.000

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 head0.016
GPT teacher head0.223
Teacher spread0.207 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2011
Admission routes2
Has abstractyes

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