MétaCan
Menu
Back to cohort
Record W1986950252 · doi:10.5558/tfc78665-5

Synthesizing knowledge of the Claybelt to promote sustainable forest management

2002· article· en· W1986950252 on OpenAlexaffvenueabout
Patrick Lefort, Brian D. Harvey, John Parton, Gwynneth Smith

Bibliographic record

VenueThe Forestry Chronicle · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversité du Québec à MontréalNatural Sciences and Engineering Research Council of CanadaMinistry of Natural Resources and ForestryUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsBiodiversitySustainable forest managementWork (physics)Forest managementForestryEnvironmental resource managementGeographyNatural resourceSustainable managementDisturbance (geology)Forest ecologyNatural forestEcosystem managementAgroforestryEcosystemEcologyEngineeringSustainabilityEnvironmental science

Abstract

fetched live from OpenAlex

A review of the scientific literature relevant to the Claybelt region was undertaken under the initiative of Lake Abitibi Model Forest (LAMF) and in collaboration with the Canadian Forest Service, the Ontario and Quebec Ministries of Natural Resources and the NSERC-UQAT-UQAM (Natural Sciences and Engineering Research Council – Université du Québec en Abitibi-Témiscamingue – Université du Québec à Montréal) Industrial Chair in Sustainable forest Management. The objective was to synthesize this information in order to develop better forestry practices and identify knowledge and research gaps. Forestry-related knowledge was gathered on six broad topics: i) natural disturbances, ii) forest ecosystems, iii) past and present forest practices, iv) biological diversity, v) forest management and vi) examples of current applications of natural disturbance-based forest management. The work allowed us to synthesize a large body of knowledge into one publication that will be a useful reference for foresters in both provinces. Key words: biodiversity, Claybelt, even-aged/uneven-aged forests, fire, silvicultural practices

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 categoriesInsufficient payload (model declined to judge)
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 score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations17
Published2002
Admission routes3
Has abstractyes

Explore more

Same venueThe Forestry ChronicleSame topicFire effects on ecosystemsFrench-language works237,207