Mineral balance plasticity of cloudberry (rubus chamaemorus) in quebec-labrador
Bibliographic record
Abstract
Copyright © 2013 Léon Etienne Parent et al. This is an open access article distributed under the Creative Commons Attribution Li-cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The “ionome”, or plant elemental signature, is the elemental composition of an organisms, that may vary with genotypic traits and phenotypic plasticity. Cloudberry (Rubus chamaemorus L.) is a circumboreal wild berry naturally growing in oligotrophic oceanic bogs of Quebec and Labrador. Our objective was to relate cloudberry stand productivity to the ionomes of female ramets and explore the cause of nutrient imbalance in low-performing stands. We analyzed 13 ele-ments in female ramets collected in 86 natural sites where crop productivity varied widely. We computed orthogonally arranged balances reflecting plant stoichiometric rules and soil biogeochemistry. Balances were expressed as isometric log ratios (ilr) between ad hoc sub-compositions. Balances were synthesized into a Mahalanobis distance optimized based on receiving operating characteristics (ROC). The critical Mahalanobis distance was found to be 5.29 for cutoff berry yield of 3.8 g·m−2 with test performance of 0.88, as measured by the area under the ROC curve. Although past research on cloudberry focused mainly on the N/P ratio, this exploratory mineral balance analysis indicated that imbal-ance in the [P,N | S,C] and [Al | Nutrients] partitions appeared to be the factors limiting the most cloudberry productiv-ity in the bogs. Some highly productive stands showed relatively high C fixation and K use efficiency. Due to the com-
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".