Durability performance evaluation of green geopolymer concrete
Bibliographic record
Abstract
The present manuscript is a state-of-the-art review, which examines the most recent stages in the developments of the class of eco-efficient green geopolymer concrete technology in the light of its history of research, more specifically, focusing on its unsettled durability criterion. The objective of this article is not merely to review it’s on hand literature but also to focus on durability attribute on establishing it as a perspective cost-effective and sustainable universal building material. According to some researchers, durability related characteristics of GPC such as alkali-silica reaction; resistances to acid attack, Sulphate attack, freeze-thaw conditions, corrosion; water absorption, permeability, porosity, sorptivity, Chloride penetration, Chloride migration test techniques, Carbonation, drying shrinkage and efflorescence necessitate more elucidations to prove its capability as durable edifice material. The suggestions mentioned in this article will be helpful for future research work on long-drawn-out durability. Although a little challenge viz., curing hurdles, practical confronts of utilization at times, restricted supply chain, and a call for vigilant command of mixture design for its manufacturing, are standing in its pathway for a quid pro quo replacement of OPC-concrete from the construction industries. Ultimately, the paper identifies research challenges, promotion and relevant discussions for this promising novel type of building material.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".