A Comparison of 2-D Molecular Tagging Velocimetry (MTV) and Micro Particle Image Velocimetry (µPIV) for Microscale Flows
Bibliographic record
Abstract
A 2-D scanning molecular tagging velocimetry technique is presented. The described MTV technique utilizes a scanning laser system enabling two-dimensional flow velocity measurements. The laser scanning system allows the tagging of molecules seeded in the flow of any desired pattern. This array of small dot markers in the region of interest is visualized using an epi-fluorescent optical imaging system. The scanning system facilitates the convenient maneuvering of the laser beam allowing the tagging of either a single point or a pattern. The laser beam is focused onto a single point leading to a more efficient tagging process. A standard particle tracking velocimetry (PTV) approach is used to resolve the two components of the flow velocity. Results obtained show the capability of the designed system to tag a region in the centre of the field of view. The tagging laser will be moved to any desired location within the field of view to tag the desired region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".