Bibliographic record
Abstract
Soil productivity is a function of inherent factors such as topography, parent material, physical and chemical properties of the soil, and the infrastructure for irrigation and drainage. As multi-criteria evaluation methods in soil productivity assessment, the least-factor and weight methods, while popular, have limitations. The least-factor method is not accurate enough in the absence of a vital constraint factor, and the weight method leads to an inaccurate, and even incorrect result when there is a vital constraint factor. In order to overcome these limitations a new concept, relative weight, was introduced and a prototype model developed. In this prototype model, every factor has different relative weights in different soil units, thus allowing it to overcome shortcomings of the Weight method where the weights of a given factor are assumed to be equal in all soil units. This prototype model was then applied in a case study on the Loess Plateau in Northwest China. Results from the case study indicated this prototype model was more precise than either the least-factor or weight methods, and was able to avoid the invalid results of the Weight method. Key words: Soil productivity index, relative weight, multi-criteria evaluation, Loess Plateau
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".