vol2bird: Vertical profiling of biological scatterers from weather radar data
Bibliographic record
Abstract
All issues included in this release can be found here. vol2bird now reads Vaisala Sigmet IRIS (Iris RAW) format, the native radar data format of Vaisala radar processors (e.g. used in Canada, Portugal, Finland) (#112) added functionality to vol2bird to read files containing single scans (sweeps) and merge them into polar volumes (#116) rsl2odim now converts Vaisala IRIS format and ODIM hdf5 format and can merge files containing scans / sweeps into a polar volume. new input argument format that allows specifying multiple input files change default maximum range from 25 km to 35 km (#117) fixed a bug that in rare cases produced a negative reflectivity eta (#123) new determineRadarFormat() function to check whether a file is in ODIM, IRIS or RSL format added a documentation webpage generated by doxygen (available at http://adokter.github.io/vol2bird) added this NEWS.md file to document releases
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.119 | 0.113 |
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".