Seeing is Believing, A Fourteen-Year Study on Efficacy and Economics of Visual Inspections to Protect A Large Mammal Collection from Insect Pests
Bibliographic record
Abstract
Abstract In response to the cessation of use of in-case fumigants, from 1995–2009 the Smithsonian Institution, National Museum of Natural History's Division of Mammals (DOM) applied a consistent voluntary visual inspection protocol over a period of 14 years. On average, per-case inspections required about 7 minutes. Inspections categorized case pest activity as clean, soiled, signs of life, and live insects. These categories compartmentalized levels of uncertainty about pest activity and directly led to remedial treatment and cleaning actions performed at a case level. Evidence of recurrent reinfestation led to case renovation or replacement. In order for an integrated pest management (IPM) method to be successful, it has to demonstrate a predatory efficacy better than the replacement and recruitment rates of the pests. With at most 1.5% of staff time devoted to IPM, case infestations of Thylodrias contractus (Motschulsky 1839) Coleoptera: Dermestidae and Necrobia rufipes (De Geer 1775) Coleoptera: Cleridae were lowered to near zero within 3 years. Rebound toward initial rates occurred after a forced 3-year hiatus in inspections and was similarly dealt with by a following round of inspections. The hourly investment of time is comparable with that of previous case repellant or fumigation regimes, but without the aggregated loss of access to collections during enclosure and out-gassing of fumigant, thus allowing longer and safer access to collections over a year, and instilling greater knowledge of specimen condition across the collection regardless of current research focus. The study also includes an economic comparison to historical methods of case level pest suppression with fumigants against two other comparably large collections documented within the last half century.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".