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Record W2222857596 · doi:10.1021/acs.cgd.5b00472

Sophisticated Nanostructure in Stone Part of Sea Urchin Tooth: Enlightenment for Artificial Composites

2015· article· en· W2222857596 on OpenAlexaff
Xinqiao Zhu, Shengnan Wang, Jingfei Deng, Rizhi Wang, Xiaoxiang Wang

Bibliographic record

VenueCrystal Growth & Design · 2015
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsUniversity of British Columbia
FundersZhejiang University
KeywordsNanostructureTransmission electron microscopyScanning electron microscopeMaterials scienceFiberCrystal (programming language)Composite materialMatrix (chemical analysis)NanotechnologySingle crystalCrystallographyChemistryComputer science

Abstract

fetched live from OpenAlex

Sea urchin teeth, which are used to scrape rocks for food, assume significant mechanical functions. Unraveling their design strategies could provide inspiration for the pursuit of high-performance artificial composites. In this work, we used scanning electron microscopy, transmission electron microscopy, and high-angle annular dark-field scanning transmission electron microscopy to probe the elaborate nanostructure in the stone part of Glyptocidaris crenularis tooth. Our results show that the mesocrystalline matrix, though diffracting as a single crystal, is composed of highly oriented nanocrystals and shares almost coincident crystal orientation with its central single-crystal fiber. Interestingly, the fiber and matrix are fitted together by numerous single-crystal nanostrips rather than being completely separated by an organic sheath. This sophisticated architecture may endow the tooth with sufficient structural stability to prevent catastrophic fractures.

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)0.001
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 score0.153
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.056
GPT teacher head0.265
Teacher spread0.209 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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