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Record W7052558542

Stand structure differences resulting from post-harvest silviculture in boreal mixedwoods / by Daniel Corbett.

2007· dissertation· en· W7052558542 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2007
Typedissertation
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsnot available
Fundersnot available
KeywordsSilvicultureChronosequenceTaigaBorealThinningForest structureStand developmentLoggingForest management
DOInot available

Abstract

fetched live from OpenAlex

Under the Ontario Forest Accord, several parcels of land have recently been designated as protected areas reducing the area available for forest management. As a result, forestry companies will likely have to intensify timber production using post harvest silviculture on remaining industrial forestry land to yield the same volumes achieved from fewer operable hectares. I used a chronosequence approach (stands 15-57 yrs) to investigate the question: "Does post-harvest silviculture change forest composition and structural attributes at the stand level?" I sampled overstory, standing dead-wood components, and woody debris of forty-three upland mesic stands in the Gordon Cosens Forest, Kapuskasing, Ontario. Stands were selected to address potential differences in structural attributes resulting from three silvicultural intensities (harvest with no silviculture, harvest with planting and with herbicide tending, and harvest with site preparation, planting, and application of herbicide), across the chronosequence.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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
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
Published2007
Admission routes1
Has abstractyes

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