Influence of Habitat Type in the Distribution and Abundance of Flying Insect Species in Kisumu National Polytechnic Implications for Food Security
Bibliographic record
Abstract
Food security is challenged by loss of natural habitats that reflect in reduction of insect population which is an alternative source of protein and a pollinator for flowering plants. The aim of this study was to assess the influence of a habitat type in the distribution and abundance of flying insects. Open-field, botanical-garden and water-shed habitats, 100 m apart were identified. Sweep net was standardized by taking 100 sweeps. Collection was done twice a week but two times a day at 0800 h and 1400 h. Sweep net was swung on short vegetation and in air, collected insects were emptied in killing jar containing 70%-chloroform soaked in cotton-wool, covered with aluminum foil. Edible insects were identified by attaching a photo to a questionnaire, administered to students, teaching and non-teaching staff. High proportion of insect was observed in Botanical garden (41%), compared to water shed (35%) and open field (24%). Mosquitoes were dominant in botanical garden (31.1%) and water shed (20.1%), while butterflies were dominant in open field (28.4%). In three habitats, mosquitoes were most abundant (23.8%). Lake-flies (27%) and grasshopper (26.7%) were highly proposed edible species. However, the profession of an individual does not influence the choice of edible insect ( P = 0.763). Botanical garden provided insect high enough, showing a great potential as a future habitat that can protect insect species to help fight food insecurity.
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 | 0.000 |
| 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) | 0.002 | 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".