Prevalence of Phosphorus, Potassium, and Calcium Limitations in White Spruce across Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT In Canada, the coniferous forest was generally found to be nitrogen (N) deficient, but base cation deficiencies may be becoming more prevalent. Newly-developed nutritional standards based on leaf nutrient concentrations and compositional nutrient diagnosis (CND) were applied on published data of white spruce nutrition from sites across Canada. Results suggest that nutritional disorders in white spruce are not restricted to N deficiencies. Based on nutrient concentrations, deficiencies are common, particularly in phosphorus (P), potassium (K), and calcium (Ca), but toxicities are rare. The CND analysis revealed some cases of excess N, P, and magnesium (Mg).
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it