Estimates of forest floor litter frog communities: A comparison of two methods
Bibliographic record
Abstract
Abstract Estimates of forest leaf litter frog density, mass, richness and diversity given by the widely used 8 m × 8 m large plot method (LPM) were compared with estimates obtained by a newly proposed method (small 2 m × 1 m plots with leaf removal; SPLR). The study site was an undisturbed area of the Atlantic Rainforest of Ilha Grande, an island located in the south of Rio de Janeiro State, Brazil. Twenty‐four LPM (totalling 1536 m2 of forest floor) and 90 SPLR (totalling 180 m2 of forest floor) were performed. The estimates obtained by the two methods differed markedly, indicating that even using a much smaller sampling area (11.7% of that of LPM), SPLR gave frog density estimates six times higher, and frog mass estimates approximately 2.5 times higher than estimates provided by LPM. The species richness and diversity obtained by the two methods were similar, despite the fact that the total area sampled with SPLR was much smaller. These data suggest that LPM may underestimate the abundance and biomass of leaf litter frogs in a given area.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".