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Record W2159233906 · doi:10.1154/1.2204056

Quantitative Rietveld analysis of hydrated cementitious systems

2006· article· en· W2159233906 on OpenAlexaff
Laura Mitchell, Jim Margeson, Pamela S. Whitfield

Bibliographic record

VenuePowder Diffraction · 2006
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsPortlanditeCementitiousAragoniteMaterials scienceCementAmorphous solidAmorphous calcium carbonateCalciteMineralogyPhase (matter)Rietveld refinementCalcium carbonateAnalytical Chemistry (journal)Chemical engineeringComposite materialChemistryCrystallographyPortland cementChromatography

Abstract

fetched live from OpenAlex

A study examining the feasibility, and possible necessity, of using transmission data from capillary mounted samples for quantitative analysis of hydrated cement systems was conducted. In order to obtain true quantitative results, the amorphous contents were determined by the addition of an internal standard. The amorphous content of the starting tricalcium silicate was found to be approximately 21–22 wt %, in close agreement with previously published results. The study revealed that the spherical harmonics preferential orientation correction may not be reliable with unmicronized hydrated cement materials in reflection geometry, as chemically unreasonable progressions in Portlandite content with time were observed. The data obtained from capillary measurements, however, exhibited little or no preferential orientation, and appeared to produce the progression of phase contents expected from the reaction. The use of capillaries would appear to be justified in some circumstances to obtain reliable quantitative results from hydrated cementitious materials. In this particular system, a significant fraction of calcium carbonate was present as aragonite, as well as the more usual calcite.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.258
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations20
Published2006
Admission routes1
Has abstractyes

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