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Record W1505771769 · doi:10.22230/jem.2010v11n3a78

Bluejoint Stand Establishment Decision Aid

2011· article· en· W1505771769 on OpenAlexaffabout
Jill Dunbar, Larry McCulloch, Richard Kabzems

Bibliographic record

VenueJournal of Ecosystems and Management · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsMinistry of Forests
Fundersnot available
KeywordsMarshGeographyAgroforestryProductivityIndigenousHabitatEcologyBiologyWetland

Abstract

fetched live from OpenAlex

Bluejoint (Calamagrostis canadensis [Michx]. Beauv.), which is also known as Canada bluejoint grass, reedgrass, marsh reed grass, and Scribner’s reed grass, is a commonly occurring indigenous grass found throughout British Columbia. Bluejoint is a natural part of many ecosystems, but openings caused by fire, flooding, insect outbreak, windfall, timber harvesting, or other larger-scale disturbances have locally increased its abundance. Bluejoint has become a problem weed species on some sites in the northeastern part of the province. Its major impact in forestry is at the stand establishment stage where it can aggressively invade disturbed sites, inhibiting natural regeneration and impeding root and shoot development of planted seedlings. Seedling mortality is often an outcome.This Stand Establishment Decision Aid (SEDA) is a synopsis of key information forest managers in northern British Columbia will need to help understand how to mitigate the impacts of bluejoint. This SEDA describes susceptible site types, hazard ratings, bluejoint development, impacts on forest productivity, other values, and appropriate management practices. The synopsis also includes a short list of references for further reading and contact information for experts on the topic.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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.

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

Citations0
Published2011
Admission routes2
Has abstractyes

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