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Record W6908108812 · doi:10.25545/5wd1ob

Simulated Mapped Plots Derived from NL Spacing Trials for Sector Subsampling Study

2020· dataset· en· W6908108812 on OpenAlexaffabout

Bibliographic record

VenueUNB Dataverse · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsBalsamAbies balsameaDiameter at breast heightRandomized block designBlack spruceBiomass (ecology)Block (permutation group theory)

Abstract

fetched live from OpenAlex

The base data were collected from 3 early spacing trials located in western Newfoundland, Canada and established in the early 1980s. The dominant species was balsam fir with minor components of black spruce and white birch. Five spacing treatments were applied in this study areas using a randomized complete block design: control, or no spacing, (S00), 1.2m spacing (S12), 1.8m spacing (S18), 2.4m spacing (S24) and 3.0m spacing (S30). Each treatment was repeated 3 times per site (3×3×5 = 45 PSPs in this study). Treatments were applied to a 0.25 ha block (50m × 50m), and a circular permanent sample plot (PSP) was established near the center of each block. Plot sizes varied so that there were approximately 100 trees per plot following treatment. All trees 1.3 m and taller were identified by species and measured for diameter at breast height (DBH, nearest 0.01cm, BH = 1.3 m) and total height (HT, nearest 0.01 m). PSPs were remeasured at 3 to 5–year intervals but only the last measurements were used here. Stemwood, bark, branch, and foliage biomass (kg) was estimated for each tree using the Canadian national biomass equations. Total above-ground biomass (BM, kg) was estimated by summing these components.

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)0.003
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.068

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 head0.228
GPT teacher head0.368
Teacher spread0.140 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes2
Has abstractyes

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Same venueUNB DataverseFrench-language works237,207