Future climatic suitability of native tree species in restoration sites in Northwestern Ecuador
Bibliographic record
Abstract
The dataset includes climatic suitability of 10 tree species in 1237 restoration sites in Northwest Ecuador under baseline climatic conditions (1960-1990) and two climate scenarios (RCP 4.5 and 8.5) in the 2030s, 2050s, and 2070s. We built bioclimatic niche models to obtain the climatic suitability values for the species at each restoration site. The suitability values ranged from 0 (unsuitable) to 1 (suitable). Suitability thresholds (i.e., MaxSS, MTP, 10% TP) per species are provided to categorize species as "suitable" or "unsuitable" at the restoration sites. We used this dataset on species climatic suitability in restoration sites to assess the species climatic viability (i.e., persistence over time). Geographical data on the restoration sites location is not publicly available due to privacy restrictions from the government of Ecuador under the permit (MAE-SG-2018-6447-E).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".