Bibliographic record
Abstract
Abstract The CGIAR System‐wide Initiative on Malaria and Agriculture, SIMA, organized a special seminar on Malaria in Irrigated Agriculture at the ICID 18th International Congress on Irrigation and Drainage, 23 July 2002, Montreal. Five oral presentations, six posters and a lively discussion provided a wealth of information on the linkages between irrigation or drainage and malaria transmission in Burkina Faso, Côte d'Ivoire, India, Malaysia, Mali, the Netherlands, Pakistan, Sri Lanka, Tanzania, and Zimbabwe. The economic impact of the disease on agricultural incomes can be quite substantial. Malaria was strongly associated with waterlogging, with poor maintenance of irrigation systems and with rice cultivation. Several presenters made recommendations for environmental measures to reduce malaria and a few reported on actually implemented interventions. Most important recommendations from the seminar were increased collaboration between the water and health sectors, and contextuality: the need to consider the context of mosquito ecology, disease and environment in every case. Only then can specific and innovative intervention approaches be identified and applied to help fight malaria. Moreover, if irrigation and drainage indeed bring economic development to the rural areas, the population will benefit in terms of better health and less malaria. Copyright © 2003 John Wiley & Sons, Ltd.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".