Bibliographic record
Abstract
This report documents the work done to enhance the Software Tools for Analysis and Research (STAR) by creating displays appropriated for data collected using towed arrays. The STAR software suite was developed to support general research and analysis objectives at Defense R&D Canada (DRDC) - Atlantic. Though relatively generic, many of the STAR displays had been tuned to meet the requirements of sonobuoy analysis with a single display pane displaying data from a single receiver / beam combination. Under this contract, three displays were added to aid in visualizing and analyzing large amounts of Energy Time Indicator (ETI) data on a single image. These summary displays provide a more intuitive view of the available information. New displays include a beam map display, a polar beam map display, and an on- demand beam clutter display. Each new display contains a single image with intensity represented by a grey-scale or color-map. For the beam map display, the time varying intensity of all beams from a single receiver is shown. On the polar map display, monostatic or multistatic data is mapped onto a geographic display. The beam clutter display maps the time varying intensity from many pings for a single receiver / beam combination onto a single image. The last display previously existed, but it can now be generated "on-the-fly". A number of display options are user-modifiable at run-time using a number of custom settings dialogues. Options include quantization selection, color scale modification and interpolation, decimation and gridding algorithm selection, to name a few. Finally, a new method of outputting data to image based Surveillance Acoustics Plotting (SAPLOT) files were implemented. This new output format will simplify formatting of figures for reports and papers.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.188 | 0.083 |
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".