Erratum for “Slender Steel Columns Strengthened Using High-Modulus CFRP Plates for Buckling Control” by Amr Shaat and Amir Z. Fam
Bibliographic record
Abstract
Amir Z. Fam, M.ASCE Professor and Canada Research Chair in Innovative and Retrofitted Structures, Dept. of Civil Engineering, Queen’s Univ., Kingston, ON, Canada, K7L 3N6. The following correction should be made to the original paper. Eq. (7) gives predictions for the average strain of the CFRP plates at failure. The strain predictions are established using three different equations depending on the range of the normalized slenderness ratio of the strengthened steel column (kL=rtρf). In the original paper, for (kL=rtρf > 315), Eq. (7) has a typographical error. The equation’s constant reads 1.07, when it should have been 0.83. As such, this equation should be corrected to read
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".