Bibliographic record
Abstract
ABSTRACT Poor soil conditions, poor construction techniques, intense foot traffic, and limited budget often make it difficult to maintain a quality turfgrass cover on many municipal athletic fields. The Carbon County Ball Field complex was built in 1978 in Price, UT. During construction, the highly saline and shallow soil was severely compacted. By 1998, the turfgrass quality had deteriorated to the point where two of the fields were unplayable. Those responsible for the maintenance of the field tried numerous remedies, all of which failed. Roy Phillips, the county extension educator, was consulted about the condition of the fields. Mr. Phillips sought advice from Dr. Jeff Andersen, the Utah state extension turf specialist. Dr. Andersen agreed that the fields needed improvement and focused on the issues of salinity, compaction, drainage, and proper irrigation. This case was designed for use in an advanced turfgrass management course, and has proven to be useful in applying management options for an athletic field, especially when considering the typically high pH, saline conditions, and soils of the arid West. The students are asked to make recommendations that Dr. Andersen should present to the county commissioner and city officials. Recommendations should involve agronomic solutions that take into account the physical, economic, and social realities of the situation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".