Evaluation of Some Secondary Radio Meteorological Variables for Line-of-Sight Applications over Some Locations in Nigeria
Bibliographic record
Abstract
Reliable data on radio propagation is required to suggest useful models for radio-climatic study. Computation of some secondary radio parameters across ten locations in Nigeria was done to deduce their effects on Line-of-Sight links. ERA-5 data obtained from the archive of European Centre for Medium-Range Weather Forecast (ECMWF) comprising of surface air and dew temperature, atmospheric pressure and relative humidity covering eight years (January 2010 – December 2017) was utilized. The results show that average radio refractivity values during the wet season (343.4 N-units) was higher than the dry season (273 N-units) and radio refractivity gradient values increase as the wet season progresses. Mean effective earth radius factor (k-factor) for the period of study were 1.38, 1.34, 1.67 and 1.72 for the rainforest, mangrove swamp, Sudan and guinea savannah regions respectively. It was also observed that a distinct relationship exists between the geo-climatic factor (K) and the seasons of the year with a range of 2.2 ×10-5 to 1.0 ×10-4.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".