ShipIR model validation using spectral measurement results from the NATO SIMVEX trial
Bibliographic record
Abstract
The ship signature model ShipIR/NTCS has been selected as a NATO standard. In 2001 Norway participated in the SIMVEX field trial arranged by NATO in Canada for validation of this model. The measurements were performed on a research vessel under different meteorological conditions, when the ship was sun illuminated and shaded, and also at night. This paper presents spectral results from our high resolution FTIR spectroradiometer, Bomem DA5. Using in-house software that enables correction of non-ideal properties of the spectroradiometer, we obtained improved absolute precision of calibrated spectra. The FTIR results are most interesting for sources with signatures deviating significantly from blackbody functions, like the ship plume, sun illuminated surfaces and sea and sky backgrounds. Ship surface and sea and sky background results have been compared with ShipIR/NTCS predictions. Results from plume measurements have been compared with simulated spectra, using the FASCODE atmospheric model, and we have estimated the plume temperature and the concentration of the most important IR contributing molecules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".