Robust Test of the Flatbed Scanner for Air-Void Characterization in Hardened Concrete
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
Abstract In the province of Ontario, Canada, the Ministry of Transportation administers a quality assurance testing program for all new concrete construction where air content and spacing factor are measured. Testing is performed by qualified operators in accordance with ASTM C457/C457M-12. In this study, 324 routine samples that had been tested by qualified operators were obtained and analyzed for air-void parameters by an alternative automated flatbed scanner method. A strong correlation was found between the manual and automated methods. This research explored the premise that summary statistics from a small set of training samples could be used to define a set of global threshold levels to measure air-void parameters from a much larger population. Two different methods for setting the global thresholds were tested: one based on arithmetic means, and another based on modal location parameters derived from type I extreme value distributions. The frequency of false-negative errors (failure to detect a defect) was used as a criterion to assess the different threshold methods. Automated test results derived using global thresholds based on arithmetic means minimized the occurrence of false-negative events.
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.
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 | 0.001 |
| 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) | 0.000 | 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 it