Proposed NRC portable target case for short-range triangulation-based 3D imaging systems characterization
Bibliographic record
Abstract
The National Research Council of Canada (NRC) is currently evaluating and designing artifacts and methods to completely characterize 3-D imaging systems. We have gathered a set of artifacts to form a low-cost portable case and provide a clearly-defined set of procedures for generating characteristic values using these artifacts. In its current version, this case is specifically designed for the characterization of short-range (standoff distance of 1 centimeter to 3 meters) triangulation-based 3-D imaging systems. The case is known as the "NRC Portable Target Case for Short-Range Triangulation-based 3-D Imaging Systems" (NRC-PTC). The artifacts in the case have been carefully chosen for their geometric, thermal, and optical properties. A set of characterization procedures are provided with these artifacts based on procedures either already in use or are based on knowledge acquired from various tests carried out by the NRC. Geometric dimensioning and tolerancing (GD&T), a well-known terminology in the industrial field, was used to define the set of tests. The following parameters of a system are characterized: dimensional properties, form properties, orientation properties, localization properties, profile properties, repeatability, intermediate precision, and reproducibility. A number of tests were performed in a special dimensional metrology laboratory to validate the capability of the NRC-PTC. The NRC-PTC will soon be subjected to reproducibility testing using an intercomparison evaluation to validate its use in different laboratories.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".