Development and testing of calibration device for differential pressure hydrostatic leveling based on liquid-level rise and fall method
Bibliographic record
Abstract
Abstract In view of the current situation that it is difficult to achieve high-precision calibration for the widely used hydrostatic leveling in engineering construction and structural monitoring, a calibration method by controlling the liquid-level rise and fall is proposed. Firstly, a calibration device for hydrostatic leveling composed of a vertical displacement stage, a micrometer resolution grating ruler, etc. is developed. Secondly, the liquid-level monitoring and compensation method and system are analyzed and constructed. The high-precision calibration experiment of the differential pressure hydrostatic leveling is designed, and the uncertainty evaluation method for the calibration of the hydrostatic leveling is given. The experimental results show that within a 3 m range, the measurement uncertainty of the calibration device is U = 0.064 mm ( k = 2), providing a key calibration technology for the hydrostatic leveling to achieve high-precision measurement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".