Bibliographic record
Abstract
Mosquito-borne illnesses exact an enormous toll on human health; malaria parasites alone currently infect approximately 500 million people, more than 1 million of whom will die this year. A. gambiae is the principal malaria vector in sub-Saharan Africa, where 90% of the world's deaths due to malaria occur. Historically, the greatest successes in prevention of malaria, yellow fever, and other mosquito-borne disease have come from controlling the mosquito vector. Current work on vector control holds much promise and can be addressed more efficiently by genomic approaches. The reference genome sequence of A. gambiae sensu stricto (a representative member of the cryptic A. gambiae species complex) has yielded novel insecticide targets, has facilitated the identification of genes involved in insecticide resistance, and has led to the identification of genes that underlie the strong preference of this vector for human blood. Germ-line transformation of the mosquito has been achieved and the reference genome sequence will facilitate efforts to develop a tractable genetic control strategy for mosquitoes. The publication of the A. gambiae genome is a landmark in medical entomology, both because this was the first vector genome to be fully sequenced and because of the impact of this mosquito on public health.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.093 | 0.105 |
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".