Effect of nursery conditioning treatments and fall fertilization on survival and early growth of <i>Pinus taeda</i> seedlings in Alabama, U.S.A.
Bibliographic record
Abstract
Four seedling conditioning treatments and four fall fertilization treatments were applied to loblolly pine (Pinus taeda L.) seedlings in a bare-root nursery in Alabama. Three conditioning treatments involved undercutting plus root wrenching (two, four, and six times), and a fourth treatment included top-pruning (three times) and no undercutting. Fertilizer treatments consisted of (i) control, (ii) 150 kg/ha of N, (iii) 150 kg/ha of N plus 150 kg/ha of P, and (iv) 150 kg/ha of K. On two sites, seedlings were planted in November, and an equal number were placed in cool storage and planted 6 weeks later in mid-December. Results 5 years after outplanting were generally similar for both sites; however, experimental error terms were higher on the sandy site. As a result, conditioning and fertilizer treatments had a statistically significant effect on volume per hectare at the loamy site but not at the sandy site. Volume per hectare was enhanced by undercutting in August followed by two root wrenchings and fall fertilization with N plus P. Storing seedlings reduced height, groundline diameter, and volume per hectare at both sites and reduced survival at the loamy site. Survival of both freshly planted and stored seedlings was greater than 71% at both sites.
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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".