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Record W2005943971 · doi:10.4236/ajps.2013.47183

Mineral Balance Plasticity of Cloudberry (<i>Rubus chamaemorus</i>) in Quebec-Labrador Bogs

2013· article· en· W2005943971 on OpenAlexaffabout
Léon Étienne Parent, Sérge-Étienne Parent, Valérie Hébert-Gentile, K Naess, Line Lapointe

Bibliographic record

VenueAmerican Journal of Plant Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsCentre Intégré de Santé et Services Sociaux de Chaudière-AppalacheUniversité LavalAgriculture and Agri-Food Canada
Fundersnot available
KeywordsChemistryInternal medicineMedicine

Abstract

fetched live from OpenAlex

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 elements 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 gm -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 imbalance in the [P,N | S,C] and [Al | Nutrients] partitions appeared to be the factors limiting the most cloudberry productivity in the bogs. Some highly productive stands showed relatively high C fixation and K use efficiency. Due to the complexity of interactions, diagnosis should be conducted computing first a global imbalance index (Mahalanobis distance), then examining in the balance domain binary partitions departing most from reference, and finally appreciating relative shortage, sufficiency or excess of elements in the concentration domain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.233
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2013
Admission routes2
Has abstractyes

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