Advances in insect physiology and endocrinology through genomics, peptidomics, and related technologies<sup>1</sup>Introduction to the virtual symposium on recent advances in understanding a variety of complex regulatory processes in insect physiology and endocrinology, including development, metabolism, cold hardiness, food intake and digestion, and diuresis, through the use of omics technologies in the postgenomic era.
Bibliographic record
Abstract
This series of the Canadian Journal of Zoology brings together scientists actively working on insect physiology and endocrinology in this postgenomic era. This issue is timely and appropriate. Timely, because of the pace of change brought about by genome projects, functional genomics and genetics (omics technologies), including gene microarrays, mutations, RNAi, and sophisticated mass spectrometry techniques, which are helping to unravel complex regulatory processes. Appropriate, because Canada, and the Canadian Journal of Zoology, has a rich history and strong tradition of cutting-edge research in insect biology—with particular strengths in insect physiology and endocrinology. The first review illustrates how these very modern omics technologies can be embraced and applied to insect physiology and endocrinology, and the subsequent reviews illustrate this in practice, with regard to insect cold hardiness, insulin signaling and stress, peptidergic control of food intake and digestion, endocrine control of diuresis, and finally allatoregulatory peptides. These reviews set the scene and context for the exciting era that we find ourselves in, and the depth of understanding that has come from this postgenomic revolution.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
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".