Core aeration of sand-based putting greens in the Lower Fraser Valley of British Columbia
Bibliographic record
Abstract
Core aeration, a management practice originally developed for soil-based putting greens, is still commonly used on sand-based greens. The study objective was to determine the effects of core aeration on soil properties of sand-based putting greens in the Lower Fraser Valley of British Columbia. The experiment was laid out as a randomized complete block design with three replications. The study treatments were regular management practices, including core aeration (CA) carried out in spring and late summer, and regular management practices, but no core aeration (NCA). Each core aeration event impacted 5% of the surface area. Treatments with and without core aeration had similar soil organic matter content, root weight density, and soil bulk density. The CA treatment was generally drier than NCA. Water infiltration was greater on CA than NCA, but only for 1 mo following core aeration. Core aeration generally reduced soil penetration resistance within the mat layer relative to treatment without this practice. On both treatments, soil penetration resistance consistently exceeded 4000 kPa below about 13 cm depth preventing deeper root growth. The limited benefits of the low-surface-area-impact core aeration on the maturing sand-based putting greens in a humid maritime climate suggest that this practice might not be worth doing (at a low surface area impact); however, additional, more detailed studies are needed to confirm this. Key words: Turf management, golf course management, soil penetration resistance, water infiltration
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".