Bibliographic record
Abstract
The conventional method of inclinometer data analysis computes the displacement components in two mutually orthogonal directions separately by using corresponding readings measured in individual directions. It is shown in this note that calculation errors, although insignificant, are induced when this method is used to interpret data measured by pendulum-type inclinometers, which are widely used as probe inclinometers in engineering practice. The inclinometer readings measured in the two directions are correlative, and they are dependent on both the angle of the inclinometer probe axis inclined to the gravity vertical and on the azimuth angle at which the probe movement direction deviates from one of the two directions. The displacement component in each direction can be interpreted more accurately by simultaneously using the tilt angles in both directions measured directly by the inclinometer probe. Relationships between the actual displacement components, the resultant displacement, the azimuth angle, and the tilt angles are derived and verified by laboratory experiments. A refined calculation procedure is proposed for interpreting the pendulum-type inclinometer readings, and the errors induced in the conventional method are analyzed.Key words: deformation, field instrumentation, ground movements, monitoring.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".