DEVELOPMENT AND APPLICATION OF CVA, DRIS, AND CND NORMS FOR THREE HYBRIDS OF<i>POPULUS MAXIMOWICZII</i>PLANTED IN SOUTHERN QUEBEC
Bibliographic record
Abstract
Plantations of hybrid poplars adapted to relatively poor soils and cold conditions are being established in abandoned fields and forest sites in southern Quebec. Hybrids of Populus maximowiczii are well adapted to these sites but little is known about their nutritional requirements. The objectives of this study were to develop nutritional norms (CVA, DRIS, CND) for three of these hybrids: 915508, Populus euramericana or canadensis X Populus maximowiczii; 3729, Populus nigra X Populus maximowiczii; and 915303, Populus maximowiczii X Populus balsamifera, and to apply the norms on some sites recently planted in southern Quebec. Six plantations (two per clone) were used for the determination of nutritional norms. In each plantation, individual trees were fertilized with nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) according to a factorial design with three levels of application for each nutrient (35 = 243 treatments). Tree diameter and height, unit foliar mass and foliar chemistry (N, P, K, Ca, and Mg) of each tree were determined two years after fertilization. CVA, DRIS and CND norms were determined using a boundary-line approach with each plantation. Nutritional norms could be established for most combinations of clones and nutrients. CVA, DRIS and CND indices produced with published optimum nutrient concentrations for hybrid poplars closely related to P. maximowiczii were generally in agreement with the ones developed in our study. Differences in nutritional norms among P. maximowiczii hybrids/clones were small but hybrid/clone specific norms could provide more precise estimates of tree nutrition. The application of the norms on some representative sites of southern Quebec revealed more frequent nutrient imbalances than true nutrient deficiencies with generally excessive Ca and Mg, and limiting N, P, and K.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".