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Record W4225695823 · doi:10.14447/jnmes.v24i4.a08

Investigation on Strength, Shrinkage and Hydrogen Ion Concentration of Magnesium Binder Blended Cement Concrete

2021· article· en· W4225695823 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Oxide Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsShrinkageMagnesiumMaterials scienceCementComposite materialMetallurgyHydrogenChemistry

Abstract

fetched live from OpenAlex

This research work is to investigate the strength, shrinkage and hydrogen ion concentration of concrete admixed with magnesium binder. The magnesium binder is manufactured through calcination process at a temperature of 1200 degree Celsius. The raw materials for the magnesium binder are magnesite (magnesium carbonate) and steatite (magnesium silicate). The calcined powder is also mixed with phosphate salt for better performance. The magnesium binder is replaced to cement in the proportion of 0% to 30% and the samples were tested in laboratory conditions from 1 day to 360 days for its strength. The shrinkage is tested until 130 days and the pH value is tested on 28 days hardened concrete samples. The results show that the magnesium binder replacement has refined effect on pore structures which attributed to the better performance in strength and shrinkage.

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 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 score0.001
Threshold uncertainty score0.454

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 head0.025
GPT teacher head0.237
Teacher spread0.212 · 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