Summary data for "Young mixed planted forests store more carbon than monocultures: a meta-analysis"
Bibliographic record
Abstract
This is the dataset used in "Young mixed planted forests store more carbon than monocultures: a meta-analysis" published in Frontiers in Forests & Global Change. The dataset contains carbon or biomass data for mixed and monoculture planted forests from 21 sites with a global coverage. We provide summary data necessary to conduct a meta-analysis: mean, standard deviation, and sample size, for each unique mixed and monoculture treatment at each study site. We indicate whether the values provided are aboveground carbon or biomass. For each treatment we also provide the species richness, age and species. We provide the longitude, latitude and country for each study site. Our study also assessed the effect of study design (experiment vs existing plantation), species origin (native vs non-native/mixed), and presence of nitrogen fixer in the mixture (N fixer present vs absent), we record the value of each of these factors. Finally, we categorised a subset of monocultures as commercial species monocultures based on the species use in that location.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".