Soil Temperature Patterns During the First Sugarcane Growth Stages Under a Different Crop Management in the Cauca River Valley, Colombia
Bibliographic record
Abstract
For several years, the Colombian sugarcane industry had sugar and ethanol as its primary products. However, during the last years, sugar mills opened a new market based on products before considered waste. This new market offers a new possibility for harvest-waste utilization. However, if the waste becomes an income source, crop management will change. Collecting sugarcane waste for its utilization in making some other products, would mean a new crop management scenario left the soil bare soil during the first stages of planting and ratoon canes. We simulated a bare soil condition using mesocosms, for the three most representative soil textures of the Cauca river valley, and we measured soil temperature at different depths during the most convenient planting season (March-April). Results demonstrated differences in soil temperature patterns, especially in sandy soils, which tend to have higher thermal amplitudes in all layers. The parameters of linear regressions that relate temperature of layers, including air temperature, give information related to the thermal properties of soils, and therefore, it is possible, under Cauca Valley conditions, in the future to infer soil temperature from air temperature.
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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 | 0.000 | 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) | 0.001 | 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 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".