Assessing ecosystem services in Neotropical dry forests: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SUMMARY There is an increasing consensus on the importance of understanding ecosystem service (ES) provision in order to facilitate decision making and the sustainable management of Neotropical dry forests (NTDFs), yet research on the ESs provided by NTDFs is limited. We identified the main existing gaps and trends in the quantification of provisioning, regulating and supporting ESs in NTDFs. Systematic web-based searches showed that research has been increasing in recent decades in NTDFs, supporting greater ES knowledge and assessment. Carbon storage and biodiversity are the main subjects under study, while ESs relating to water and soil lack investigation. The most common approaches for assessing ES were fauna and plant inventories, carbon dynamics and ecological processes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it