Perceived Effect of Climate Variation on Poultry Production in Oke Ogun Area of Oyo State
Bibliographic record
Abstract
Climate variation is posing a threat to livestock production, especially the poultry enterprise. This study examined perceived effects of climate variation on poultry production in Oke Ogun area of Oyo State. One hundred and eighty poultry farmers were sampled for this study. Data were collected with interview schedule, described with frequencies and percentages, and analysed with chi-square. Result shows that 81.7% of the poultry farmers were male, 73.3% were married, and 8.3% had tertiary education. Most of the poultry farmers were aware of high temperature, change in rainfall pattern and intensity, loss of biodiversity and environmental degradation. Radio, friends, and family were their main sources of information on climate variation. Some of the effects of climate variation on poultry production were increase in feed intake of birds, outbreak of pests and diseases, and decrease in poultry products. Changes in feed formulation, use of well ventilated housing system and provision of more water ad-libitum were some of the measures taken to control these effects. It is concluded that the more the education and income of poultry farmers, the higher the measures used in controlling the effects of climate variation. Poultry farmers should be well informed on the best practices to reduce the adverse effect of climate variation on poultry enterprise to ensure continual production in changing times.
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 | 0.000 |
| Science and technology studies | 0.001 | 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".