Detection and monitoring of bed bugs (Hemiptera: Cimicidae): review of the underlying science, existing products and future prospects
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
Bed bugs, Cimex lectularius L. and C. hemipterus (F.) (Hemiptera: Cimicidae) are hematophagous ectoparasites of humans. Since the resurgence of bed bugs in the late 1990s there has been a corresponding emphasis on development and implementation of integrated pest management (IPM) programs to manage infestations. One critical requirement of IPM is the ability to detect and monitor the target pest. We outline and describe the majority of all known existing devices and technologies developed for bed bug detection and monitoring as well as much of the underlying science. Almost 40 detection and monitoring products have flooded the marketplace, but for various reasons, including price, size, complexity and lack of independent scientific evaluation, they have not been widely adopted for IPM in structures. One product, the ClimbUp® Insect Interceptor, has nine competitors that utilize a similar design. This review also discloses many other technologies and products that are either too expensive or too impractical for use as either consumer or industrial products. We conclude that there is a critical need for inexpensive and effective detection and monitoring traps and lures suitable for widespread adoption by the urban pest control industry. © 2021 Society of Chemical Industry.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| 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