Exponential increase of publications related to soil water repellency
Bibliographic record
Abstract
Soil water repellency is much more wide-spread than formerly thought. During the last decades, it has been a topic of study for soil scientists and hydrologists in at least 21 States of the USA, in Canada, Australia, New Zealand, Mexico, Colombia, Chile, Congo, Nepal, India, Hong Kong, Taiwan, China, Ecuador, Venezuela, Brazil, Mali, Japan, Israel, Turkey, Egypt, South Africa, Germany, The Netherlands, Spain, Portugal, United Kingdom, Denmark, Sweden, Finland, Poland, Slovakia, Russia, France, Italy, and Greece. Although, water repellent soils already have been indicated at the end of the nineteenth century, they have been discovered and studied in most countries in the last decades. Water repellency is most common in sandy soils with grass cover and in nature reserves, but has also been observed in loam, heavy clay, peat, and volcanic ash soils. From 1940 to 1970 research was focussed on identifying vegetation types responsible for inducing water repellency and on developing techniques to quantify the degree of water repellency. Of special interest has been the effects of wildfire on the development of soil water repellency and its consequences for soil erosion. Due to increasing concern over the threat to surface and groundwater posed by the use of agrichemicals and organic fertilisers, studies on water repellent soils have also been focused on its typical flow behavior with runoff and the existence of preferential flow paths. Since the end of the 1950s, wetting agents and clay amendments have been studied to ameliorate water repellent soils. Since 1883, more than 1200 articles related to soil water repellency have been published in journals, reports, and theses. An exponential increase in number of publications started in 1960, resulting in an average of 200 publications per 5 years.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.018 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 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".