Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties
Bibliographic record
Abstract
Fox, C. A., Tarnocai, C., Broll, G., Joschko, M., Kroetsch, D. and Kenney, E. 2014. Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties. Can. J. Soil Sci. 94: 189-208. Taxonomic protocols for A horizon description are limited when detailed monitoring of soil change in dynamic soil properties is required for determining the effectiveness of best management practices, remediation efforts, and assessing subtle impacts on soil properties from environmental and anthropogenic stressors. The A Horizon Framework was designed by consolidating protocols from national and international description systems and expert opinion to optimize descriptive capability through use of additional enhanced lowercase designators. The Framework defines new protocols and syntax resulting in a unique soil fingerprint code. Five levels of enhanced lowercase A horizon designators are defined: Level 1, Soil processes and environmental context; Level 2, Soil structure-bulk density; Level 3, Organic carbon; Level 4, pH and electrical conductivity; and, Level 5, Soil and landscape context (i.e., soil texture, surface conditions, current land use, slope character). An electronic Field Form based on the new Framework syntax automatically records the soil fingerprint code in an enhanced (all Levels included) and a minimum detail mode focused on the key dynamic properties. The soil fingerprint codes become a powerful tool by which to identify trends of soil change and small alterations in the dynamic soil properties. Examples of soil fingerprint codes from selected Canada and Germany long-term experimental studies are presented.
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 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 | 0.000 | 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) | 0.000 | 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".