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Record W2087490092 · doi:10.4236/ampc.2013.31a015

X-Ray Diffraction Is a Promising Tool to Characterize Coral Skeletons

2013· article· en· W2087490092 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.

Bibliographic record

VenueAdvances in Materials Physics and Chemistry · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiomineralizationAragoniteCalciteCoralCalcium carbonateMineralDiffractionMaterials scienceCarbonateCrystal (programming language)MineralogyGeologyComputer sciencePaleontologyOceanographyPhysicsMetallurgyComposite materialOptics

Abstract

fetched live from OpenAlex

The skeletons of corals are made of calcium carbonate by biomineralization process, in the form of aragonite or calcite. To understand the characteristics of coral skeletons, especially mineralogy, crystal phases, organization and structure in individual species, X-ray powder diffraction techniques have gained increased interest in recent years as useful non-destructive tools. This review provides an overview on the recent progress in this field and briefly introduces the related experimental approach. The application of X-ray diffraction (XRD) to elucidating the structural and mechanical properties of mineral crystals in corals is reviewed in terms of characterization of CaCO3 crystal orientation. In addition, we discuss how this technique has increased our understanding of the function of the organic matrix proteins of calcified coral skeletons during mineral formation. Such information is helpful in deducing the mechanical and structural model of corals with respect to biomineralization system of skeletons.

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 score0.006
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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.238
Teacher spread0.230 · 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