Expression of uncertainty in experimental hydrodynamics with application to instrument calibration
Bibliographic record
Abstract
This is a summary for the general guidelines proposed to the 26th ITTC (2008) to evaluate and express uncertainty in measurements, in naval architecture experimental measurements, offshore technology testing, and experimental hydrodynamics. Traditionally, up to now-2008, ITTC adopted Uncertainty Analysis (UA) procedures that were based on AIAA methodologies. However, due to pressure from international laboratories, new UA procedures based on the ISO (1995) are proposed for the evaluation of uncertainties in experimental hydrodynamics. The information in this report shows the main steps for how the ISO (1995) guidelines are used to calculate uncertainties in experimental hydrodynamics and ocean technology tank testing. The guidelines provided in this report are also applicable to the evaluation of uncertainties associated with conceptual design, set up of actual experiments, methods of measurements, instruments calibrations, Data Acquisition Systems (DAS), and reporting. Example applications include calibration of instruments (a commercial vertical gyroscope in roll), characterization of flow speed in a water tunnel, and uncertainties in standard captive model testing (standard resistance tests).
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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 | 0.024 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".