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Proton Spin–Spin Relaxation Study of the Effect of Temperature on White Cement Hydration

2007· article· en· W2105650320 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

VenueJournal of the American Ceramic Society · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCalcium silicate hydrateHydrateCementProtonRelaxation (psychology)Nuclear magnetic resonanceHydration reactionChemistryProton spin crisisMaterials scienceSpin–spin relaxationSpin–lattice relaxationMineralogyAnalytical Chemistry (journal)Composite materialOrganic chemistry

Abstract

fetched live from OpenAlex

The chemical and microstructural changes within a white cement paste were characterized in situ using proton nuclear magnetic resonance spin–spin relaxation at 30 MHz, and X‐ray diffraction. Paste samples with a water‐to‐cement ratio of 0.42 were cured at constant temperatures of 2°, 20°, 60°, and 100°C. Proton nuclear magnetic resonance spin–spin relaxation allows tracking the evolution of the mixing water into the solid fractions of calcium silicate hydrate, calcium hydroxide, and monosulfate, and the liquid phases: the calcium silicate hydrate interlayer water, gel pore water, and capillary pore water. It is shown that the hydration process is markedly accelerated with increasing hydration temperature, and that proton nuclear magnetic resonance relaxation measurements can quantitatively determine the proportions of water phases, their magnetic resonance characteristics, as well as the setting times of the cement during the hydration process.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.215

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 head0.005
GPT teacher head0.316
Teacher spread0.311 · 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