Bibliographic record
Abstract
The discipline of soil science is experiencing a profound crisis. Every few months, it seems, another soil science department in some university in the world changes its name to one in which the word “soil” no longer appears. Growing numbers of researchers are also lobbying for newly-concocted expressions like “hydropedol-ogy” or “critical zone science” to replace the allegedly outmoded appellation of “soil science.” These trends are accompanied by a sharp decrease in the clientele of most soil science programs. Results of institutional and graduate student surveys carried out in 1992 and 2004 indicate that enrollment in M.Sc. and Ph.D. programs in soil science in U.S. and Canadian universities has dropped on average by about 40 percent during the past decade (Baveye et al., 2006). Similar declines are also manifest in other countries, such as the United Kingdom, where most university-based soil science units have disappeared. In terms of publications, the number of peer-reviewed articles on soils-related issues published every year has grown exponentially in the last two decades, with a very significant acceleration in the last five years. There is undeniable interest in soils …
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.040 | 0.009 |
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".