Guidelines for improved quantification and reporting of carbon stocks and additional carbon storage in agroforestry systems
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
Abstract The number of scientific publications related to biomass carbon or soil organic carbon under various land management practices has globally and dramatically increased during the last two decades, the same applies to the peer reviewed Agroforestry Systems journal. However, the quality of papers on carbon sequestration in agroforestry systems is very heterogeneous, and many studies do not fulfil simple requirements that would ensure the scientific value of these studies, resulting in high rates of rejections before and after review. The aim of this paper, co-authored by the Editor-in-Chief and Associate Editors of the Agroforestry Systems journal is to provide some basic guidelines to improve the quantification and reporting of carbon stocks and additional carbon storage in agroforestry systems, and to maximize manuscript acceptance. These guidelines are also of use for any other international peer-reviewed journal publishing studies on this topic. We also provide a checklist, for both authors and reviewers, of compulsory and recommended variables to be included before submission of an original study related to soil and/or biomass carbon stocks and sequestration in agroforestry systems.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it