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Record W2252304084 · doi:10.1016/j.envpol.2016.01.050

Metallic nickel nanoparticles and their effect on the embryonic development of the sea urchin Paracentrotus lividus

2016· article· en· W2252304084 on OpenAlexfundno aff
Julia Maxi Kanold, Jiabin Wang, Franz Brümmer, Lidija Šiller

Bibliographic record

VenueEnvironmental Pollution · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsnot available
FundersUniversität StuttgartEngineering and Physical Sciences Research CouncilRyerson University
KeywordsParacentrotus lividusNickelSea urchinMetalHigh-resolution transmission electron microscopyNanoparticleSeawaterEnvironmental chemistryMetal ions in aqueous solutionChemistryNuclear chemistryNanotechnologyMaterials scienceMetallurgyBiologyEcologyTransmission electron microscopy

Abstract

fetched live from OpenAlex

The presence of nanoparticles in many industrial applications and daily products is making it nowadays crucial to assess their impact when exposed to the environment. Metallic nickel nanoparticles (Ni NPs) are of high industrial interest due to their ability to catalyze the reversible hydration of CO2 to carbonic acid at ambient conditions. We characterized metallic Ni NPs by XRD, HRTEM and EDS and determined the solubility of free nickel ions from 3 mg/L metallic Ni NPs in seawater by ICP-MS over 96 h, which was below 3%. Further, embryonic development of the sea urchin Paracentrotus lividus was investigated for 48 h in the presence of metallic Ni NPs (0.03 mg/L to 3 mg/L), but no lethal effects were observed. However, 3 mg/L metallic Ni NPs caused a size reduction similar to 1.2 mg/L NiCl2*6 H2O. The obtained results contribute to current studies on metallic Ni NPs and point to their consequences for the marine ecosystem.

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 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 score0.091
Threshold uncertainty score0.282

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)0.0000.000

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 head0.010
GPT teacher head0.194
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations41
Published2016
Admission routes1
Has abstractyes

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