MULTIPLE TECHNIQUES CONFIRM ELEVATIONAL DIFFERENCES IN INSECT SIZE THAT MAY INFLUENCE SPIDER SOCIALITY
Bibliographic record
Abstract
Social and subsocial spiders of the genus Anelosimus exhibit an altitudinal pattern in their geographic distribution at tropical latitudes in the Americas. Social species, which capture prey cooperatively, occur primarily in the lowland rain forest and are absent from higher elevations, whereas subsocial species are common at higher elevations but absent from the lowland rain forest. Previous studies have suggested that differences in the size of potential insect prey along altitudinal gradients may explain this pattern as insects were found to be, on average, larger in lowland rain forests than at higher elevations. These studies, however, may have under-sampled the insect size composition of each habitat because only one sampling technique was used. Using a number of collection methods we sampled the insect size composition in the environments of social and subsocial spiders in this genus. We found that the average insect size in lowland rain forest habitats was indeed larger than at high-elevation cloud forests in eastern Ecuador. We also found that, even though the various techniques differed in the size of the insects they captured (visual searching and blacklighting yielding larger insects than beating, sweeping, or malaise trapping), they all caught, on average, larger insects in the lowlands. Overall, spider colonies in the lowlands caught larger prey than did spider colonies at higher elevations, paralleling differences in insect size distribution obtained by the various techniques in their respective environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".