Nitrogen diagnosis of Christmas tree needle greenness
Bibliographic record
Abstract
Christmas tree (Abies balsamea L.) fertilization is generally guided by needle colour or chemical analysis. Our objective was to develop critical values for the traditional critical nutrient range (CNR) and the compositional nutrient diagnosis (CND) of Christmas tree needles for the Quebec Appalachians. We collected survey specimens (n = 174) and obtained a validation dataset made up of 10 paired dark green and pale green stands. The compositional simplex for CND comprised five nutrient concentration values (N, K, P, Ca, and Mg) and a filling value R5 computed from differences between the whole tissue composition (i.e., 1000 g kg-1) and the known nutrient concentration values expressed in g kg-1. Nutrient multi-ratios were computed as the natural logarithm of the ratio of one nutrient concentration value to the geometric mean of all nutrients and the R5. Nutrient indexes (IN1, …, IR5) were computed as standard variables usin the mean and the standard variation of nutrient multi-ratios for the high-greenness sub-population. A nutrient imbalance index, CNDr2, was computed as the sum of squared CND indexes. Needle colour was assessed using a colour chart and a SPAD-502 chlorophyll meter. The critical SPAD value was set at 48–50 for a high greenness rating in the survey dataset, and the high-greenness sub-population comprised 95 specimens. Nitrogen and P concentrations were highly correlated to each other. Critical concentrations were found to be 17.8 g N kg-1, and 1.8 g P kg-1. CND diagnosis of the validation dataset was similar to CNR, but CND classified nutrients in the order of their limitation to colour rating. Using the validation dataset, critical values were 17.2 g N kg-1 and −1.015 as IN. The validated critical CNDr2 for five nutrients (N, K, P, Ca, and Mg) was 12.6, which was close to the critical CNDr2 value using the survey dataset (11.6) and to the theoretical χ2 value of 11.1 (P < 0.05). Key words: Tissue analysis, nutrient diagnosis, chlorophyll index, nutrient imbalance index
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".