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Record W6944116692 · doi:10.17632/fgwftw936z

Nine-years effect of harvesting and mechanical site preparation on bryophyte decomposition and carbon stocks in a boreal forested peatland

2023· dataset· en· W6944116692 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSphagnumPeatBryophyteBorealDecompositionSoil carbonPermafrostMireHumusTable (database)

Abstract

fetched live from OpenAlex

The data and code were used to assess the nine-year effects of silvicultural treatments of different intensity (harvesting and harvesting followed by mechanical site preparation) on the decomposition rates of common bryophyte’s species and on soil C stocks. The study area is located in the Clay Belt region of northwestern Quebec (Canada). There are two databases related to: (1) decompostion rate and (2) to soil C stocks. The first database contains 487 mass loss percent of three bryophytes species (Pleurozium schreberi, Sphagnum capillifolium, and Sphagnum fuscum) for one and two growing seasons (i.e., 4 months and 16 months, June to October 2019 and June 2019 to October 2020) and some micro-environmental variables. the microenvironmental variables involved, the Air and soil temperature, soil layer types (fibric, mesic, humic and mineral), water table fluctuations, organic layer thickness and canopy openness. The other database concerned soil carbon stock. There are 3 codes: one code regroups the analysis on decomposition, Principal component analysis and C stoks analysis. The second code on common variables declaration on data of decay rate and the last is on the path analysis.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.338
Teacher spread0.310 · 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 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
Published2023
Admission routes1
Has abstractyes

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