Origins and History of Laboratory Insect Stocks in a Multispecies Insect Production Facility, With the Proposal of Standardized Nomenclature and Designation of Formal Standard Names
Bibliographic record
Abstract
Laboratory insect colonies are an essential part of experimental insect science. Formalized naming of laboratory stocks is standard practice in model organisms such as mice and fruit flies, but crucial details such as colony origin and standard names are often lacking in nonmodel systems. For institutions involved in rearing multiple nonmodel species, effective monitoring requires standardized naming and nomenclature, from establishment to production, distribution, and publication. Insect rearing has been the cornerstone of the Insect Production and Quarantine Laboratories (IPQL) at the Great Lakes Forestry Centre for over 70 yr, but the histories of the insect colonies in this facility have not been adequately documented and formal, standardized names do not exist. We propose a standardized naming framework that we applied to the eight species reared at the IPQL to rectify these deficiencies. We also present the origin and history of each colony, essential information that is challenging to obtain post hoc. We suggest that other research institutions consider developing similar standards, so they can accurately document, communicate, and track laboratory insect their within the facilities and through the scientific literature.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".