Bibliographic record
Abstract
The research concentrated on the corrosion resistance of reinforced self-consolidating concrete (SCC), lightweight SCC (LWSCC), fiber reinforced LWSCC (FRLWSCC), Engineered cementitious composite (ECC) and composite (ECC-SCC/LWSCC) beams. The performance of corroded beams were analyzed based on current measurements, half-cell potential readings, crack pattern/width, rebar mass loss and diameter reduction from accelerated corrosion tests. Corroded and their companion uncorroded beams were tested to failure under four-point loading to evaluate load-deflection response, crack pattern, 1st flexure/diagonal cracking load, failure load and failure modes. Composite beams with higher ECC layer thickness exhibited superior corrosion resistance than their lower thickness counterparts and full depth SCC or LWSCC counterparts as well as performance of beams with ECC wrap was better than those with layer. Overall, ECC beams can be a superior alternative of their conventional counterparts and ECC can be used as layer or wrapping in conventional/LWSCC beams to enhance corrosion resistance and structural performance
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".