Recent Trends in Temperature and Relative Humidity in Bawku East, Northern Ghana
Bibliographic record
Abstract
Extensive analyses of trends in mean annual and mean seasonal minimum and maximum temperatures and relative humidity were examined for Bawku East, northern Ghana, for the period 1961 to 2012. Mean monthly maximum and minimum temperatures were used to analyse and establish recent temperature trends on an annual and seasonal basis. The year was divided into rainy and dry seasons for the seasonal trends. Mean monthly relative humidity at 6 am and 3 pm from 1961 to 2012 were considered to show recent trends in humidity since temperature and humidity interact to determine the heat exposure for outdoor workers. Regression analysis was used to illustrate trends and calculate mean yearly and seasonal rate of change. A Durbin-Watson statistical test was employed to verify autocorrelation of the residuals of the trend models and none was detected. Results showed a gradual and statistically significant rise in both mean minimum and mean maximum temperatures at two stations (Manga and Garu). There was an inconsistent pattern of trend observed at the third station (Binduri). Declining trends in relative humidity were observed at 6 am and 3 pm at seasonal and annual levels at Binduri and Garu, while there was a rising trend in relative humidity at Manga. The importance of this study hinges on the linkage between heat exposure (temperature and air humidity) and human health in the wake of climate change on outdoor farmers in developing countries who spend many hours doing manual work in the heat. On the whole, the rising temperature has impacted on ecosystem services in the study area.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".