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Record W6969111279 · doi:10.5683/sp/dorhf8

Soil nitrogen availability, CO2 exchange, environmental measurements of a High Arctic wetland across growing season (2016)

2018· dataset· en· W6969111279 on OpenAlexaff

Bibliographic record

VenueBorealis · 2018
Typedataset
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsQueen's University
Fundersnot available
KeywordsArcticWetlandEcosystem respirationEcosystemGrowing seasonSoil respirationNitrogenWatershedSoil carbon

Abstract

fetched live from OpenAlex

The data set was collected as an ongoing study at the Cape Bounty Arctic Watershed Observatory examining the environmental controls over spatial patterns of soil nitrogen availability in a High Arctic wet sedge meadow and how they influence carbon exchange processes to predict whether this feedback will develop. The goal of the study is to characterize the relationships between plant-available nitrogen and productivity and to see how these relationships are manifested in hyperspectral signatures. These data files contain soil nitrogen availability, carbon dioxide exchange, and environmental measurements of a High Arctic wetland across the growing season. Soil inorganic nitrogen concentrations were measured by ion exchange resin membranes and analyzed using automated flow colourimetry. Net ecosystem exchange and ecosystem respiration were measured using closed, static chambers according to methods in Beamish et al. (2014). Environmental measurements (soil moisture, soil temperature, and active layer depth) were taken twice weekly at site adjacent to the locations of the ion exchange resins.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.008

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 head0.025
GPT teacher head0.241
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2018
Admission routes1
Has abstractyes

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