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Record W6944517914 · doi:10.18739/a2qn5zc4k

Soil properties in alpine tundra, Kluane Lake, Yukon Territory, Canada (2015-2018)

2020· dataset· en· W6944517914 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2020
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsMineralization (soil science)NutrientBiomass (ecology)Soil carbonSoil respirationTotal organic carbonSoil organic matterSoil testSoil biodiversityNitrogen

Abstract

fetched live from OpenAlex

In this 4-year study we experimentally manipulated shrub presence (shrub present or removed) and litter quantity (none, natural abundance, and 2x natural abundance) in a fully factorial design. We examined a number of response variables including; physical properties (soil temperature, soil moisture, photosynthetically active radiation (PAR) and pH of both organic and mineral soil layers), nutrients (available nutrients (ammonium (NH4+), nitrate (NO3-), phosphate (PO43-)), extractable organic carbon (EOC), extractable total nitrogen (ETN), and soil total %C and %N), and microbial processes (microbial biomass (microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial biomass phosphate (MBP)), extracellular enzyme (exo-enzyme) activity, nitrogen mineralization rates (N-Mineralization), and soil respiration (root + microbial respiration)). All soil and ecosystem sampling occurred during the growing season (June – August) of 2015 – 2018 with the exception of soil temperature, which was recorded year round.

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)0.001
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.181
Teacher spread0.159 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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Same venueCalifornia Digital LibrarySame topicClimate change and permafrostFrench-language works237,207