Bibliographic record
Abstract
One of the major problems in reviewing this topic is defining the term adaptation. Unfortunately, biologists have often used the word adaptation to mean various, quite different things. However, for the purpose of this paper I will use the definition accepted by the majority of modern ecologists i.e. an adaptation is any morphological, physiological, sensory, developmental or behavioural character that enhances survival and reproduction success of an organism (Lincoln el al. 1998). This subject matter was not covered in any of the review papers of Volume 48 of the Journal in 1951 (50 years of entomology in BC), so I will take it upon myself to cover the last 100 years of research on arthropod adaptations in BC- not that there is much to report from before the 1960s 1 Since many aspects of adaptation research are likely to be covered in the other invited contributions to this issue, for example in forest entomology, insect population ecology, behavioural and chemical ecology, etc. I will concentrate my efforts in the field of eco-physiology which is, after all, the closest to my primary area of research. The paper will include not only work done by BC entomologists but also work done on BC insects by BC and other entomologists, and it will be written in chronological order, as far as is
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".