DEVELOPMENT OF DUAL NUTRIENT DIAGNOSIS RATIOS FOR BASSWOOD, AMERICAN BEECH, AND WHITE ASH
Bibliographic record
Abstract
Foliar analysis of natural deciduous tree species of basswood (Tilia americana L.) (BA), American beech (Acer grandifolia Enrh) (BE), and white ash (Fraxinus americana L.) (WA) was carried out in 1994 in southern Quebec. The Diagnosis and Recommendation Integrated System (DRIS) was developed from the traditional method to find the preliminary norm and indices of N, P, K, Ca, and Mg for the above species. The growth decade 1983-1994 in a high yielding sub-population was used to develop DRIS norms for the identification of DRIS functions and indices in relatively depleted levels of those elements in the declined growth of three species. Foliar nutrient deficiencies were found with K (-3.72) and N (-2.96) for basswood, Ca (-10.43) and Mg (-4.93) for beech, and N (-6.16), Ca (-2.56) and K (-2.05) for white ash. The DRIS analysis indicated that basswood and white ash were relatively depleted of K and N, while beech had a deficiency of Ca and Mg, and white ash had a limitation of N. These results suggest the usefulness of DRIS for foliar tissue analysis as an indicator of nutritional status and elemental stresses in natural forests. The DRIS indices were also discussed from the traditional approach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".