Saprolite: A bibliometric study from 1990 to 2020
Bibliographic record
Abstract
Saprolite is the in situ weathered rock that maintains at least some of the original rock structure. It is the deepest section of the Critical Zone and has several roles such as a source of nutrients for plants, water retention and filtering, and as a major contributor to the Silicate Carbon Sink (SCS). The consumption of CO2 by silicate weathering is uneven around the globe, therefore, it is worth to map the distribution of scientific literature, research organizations and authors which work was focused on saprolite research to identify areas potentially overlooked. This bibliometric study encompasses the literature from 1990 to 2020 indexed in the Web of Science (WOS) database. A total of 1491 scientific articles were retrieved, and 48.0% were published in the last decade. The number of papers about saprolite increased along the studied period, except for the 2010–2014 years. The top five countries in number of publications were USA, France, Australia, Brazil, and China. The USA leads the number of publications, with 5 out of the top 10 publishing institutes, and 4 out of the 10 most productive authors. Comparing the number of publications and the size of the SCS (Zhang et al., 2021), Brazil was the only country ranked top five in both lists, while India, China, USA, and Australia ranked in the top ten countries in both lists. Southern Asia and Africa are the regions in which the large SCS is most discrepant from the small number of papers published, holding great potential for new achievements.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.022 | 0.048 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".