Bibliographic record
Abstract
Proper curing of concrete is important to ensure that it achieves its intended performance and durability. Conventionally, this is achieved through external curing, applied after mixing, placing and finishing [1]. As demonstrated in the previous chapters of the present report, internal curing (IC) is potentially a very promising tool in providing additional moisture in concrete for a more effective hydration of the cement. This chapter summarizes the main benefits of internal curing and presents case studies in which those benefits could be observed in existing concrete structures.Since the 1950?s, internal curing had been inadvertently accomplished in lightweight concrete structures before its potential for reducing self-desiccation in high-performance concrete (HPC) was recognized later in the 1990?s [2]. Low-density aggregates were primarily used to reduce the mass of concrete structures. In most applications, the aggregate was saturated prior to mixing to ensure adequate workability, as it was recognized that dry porous aggregate could absorb some of the mix water during concrete fabrication and placement [3,4,5]. Lightweight concrete with a density ranging from 1440 to 1840 kg/m3 has been used in bridge decks, marine structures and other structures [6]. It was shown to achieve long-term durability from the excellent in-service performance observed in the field [7,8]. Improved cement hydration due to internal curing is one of the benefits of using lightweight concrete in structures among other benefits related to design and construction, such as: structural efficiency, seismic performance, constructability, repair, durability and economic considerations [7,9].
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".