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Record W2004265500 · doi:10.5558/tfc84756-5

Ontario's Forestry Research Partnership: Progress and next steps

2008· article· en· W2004265500 on OpenAlexaffvenueabout
James A. Baker, Frederick W. Bell, Al Stinson

Bibliographic record

VenueThe Forestry Chronicle · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsOntario Forest Research InstituteMinistry of Natural Resources and ForestryMinistry of Agriculture, Food and Rural Affairs
Fundersnot available
KeywordsGeneral partnershipAdaptive managementDocumentationForest managementBusinessForestryEnvironmental resource managementProcess managementComputer scienceKnowledge managementEnvironmental planningGeographyEnvironmental science

Abstract

fetched live from OpenAlex

This paper provides a synthesis of a 2-phase approach used by the Canadian Ecology Centre – Forestry Research Partnership (CEC-FRP) to implement adaptive management on 6 forest management units in northeastern Ontario. It also provides a summary of a self evaluation of the partnership using a set of attributes deemed necessary to successfully implement adaptive management (i.e., leadership; alignment with organizational goals; commitment, will, and capacity to act; and formal and explicit documentation). We conclude that the adoption of the 2-phase approach, rather than direct implementation of adaptive management, provided the partners with the means to identify and address critical uncertainties related to intensifying forest management on Crown lands in Ontario, focus research and transfer activities, develop and test new landscape- and stand-level models, and adjust forest management policies and practices. Key words: adaptive management, intensive forest management, knowledge transfer

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)0.014
metaresearch head score (Gemma)0.009
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: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.002
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.074
GPT teacher head0.314
Teacher spread0.240 · 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
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

Citations6
Published2008
Admission routes3
Has abstractyes

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