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Record W2971301220 · doi:10.2134/jnrlse.2003.0080

Decision Case: The Carbon County Ball Fields

2003· article· en· W2971301220 on OpenAlexaff
Paul G. Johnson, Marlon B. Winger

Bibliographic record

VenueJournal of natural resources and life sciences education · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsPricewaterhouseCoopers (Canada)
FundersUtah Agricultural Experiment Station
KeywordsDrainageEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.265
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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