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Record W2779140174 · doi:10.1139/cjb-2017-0154

Nitrate and ammonium uptake in 21 common species of moss from Vancouver Island, British Columbia

2017· article· en· W2779140174 on OpenAlexaffvenueabout
B. J. Hawkins, E. May, Samantha Robbins

Bibliographic record

VenueBotany · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMossAmmoniumNitrateBiologyEcosystemBotanyNutrientEcologyEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

Mosses play key ecological roles in water and nutrient retention in many ecosystems, yet relatively little is known of the functional characteristics of moss species, particularly nutritional characteristics. We investigated the net flux of ammonium, nitrate, and protons, using a microelectrode ion flux measurement system, in the gametophytes of 21 common species of moss from three contrasting locations in southern coastal British Columbia. The general location from which mosses were collected did not significantly affect ammonium or nitrate uptake. Proton efflux was greatest in mosses from locations with high rainfall. Rates of nitrate uptake differed among moss families, but there were no significant differences in uptake among species within families. Ammonium net flux differed among moss families, but also among species nested within family, with some species showing uptake and other showing ammonium efflux. In general, moss species native to dry habitats appeared to have higher rates of nitrogen uptake when ammonium and nitrate were available under favourable conditions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2017
Admission routes3
Has abstractyes

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