Shear strength evaluation of reinforced recycled aggregate concrete beams
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.
Bibliographic record
Abstract
A theoretical study is conducted to investigate the shear behaviour of recycled aggregate concrete (RAC) beams with and without shear reinforcements along with the performance evaluation various Code based/other existing equations in predicting shear strength. In addition, three artificial neural network (ANN) models for shear strength prediction of RAC beams with and without shear reinforcements are developed and their performance validated by using 108 beams from available research studies. Most of the Codes and existing methods underestimate the shear capacity of RAC beams with/without shear reinforcement. However, over estimation of shear strength by Codes/existing methods for about 10% RAC beams needs to be addressed when using such Codes/existing methods for shear strength prediction. All three ANN models are found to predict shear strength of RAC beams. Developed ANN models are able to simulate the effect of shear reinforcement on the shear strength of RAC beams.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it