Striga Infestation in Kenya: Status, Distribution and Management Options
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p><em>Striga</em> spp. is considered to be the greatest biological constraint to food production in sub-Saharan Africa, a more serious problem than insects, birds and plant diseases. They are among the most specialized root-parasitic plants inflicting serious injury to their host depriving them water, minerals and photosynthate. The greatest diversity of <em>Striga </em>spp. occurs in grassland. However, <em>Striga hermonthica</em> mainly occurs in farmland infecting grasses. The parasite devastating effect is accomplished prior to its emergence from the soil. It may cause yield losses in cereals ranging from 15% under favourable conditions to 100% where several stress factors are involved, thereby affecting the livelihood of millions of resource-poor farmers. Piecemeal approach to address one aspect of <em>Striga</em> problem at a time has been a setback in technology transfer to producers. Future <em>Striga</em> control programs should not be conducted separately, but should rather be conducted in an integrated approach that combines research talents of various institutions. This will facilitate collaborative research and achieve qualitative interaction between stakeholders, which can easily produce reliable technologies that are practical and available to farmers. <em>Striga</em> being a pervasive pest, time is of essence in controlling it. There is an urgent need for the establishment of policies to promote, implement, and ensure a long-term sustainable <em>Striga</em> control program.</p>
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it