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Record W1877764938 · doi:10.1139/b2012-034

Boreal forests of eastern Canada revisited: old growth, nonfire disturbances, forest succession, and biodiversity

2012· article· en· W1877764938 on OpenAlexaffvenueabout
Yves Bergeron, Nicole J. Fenton

Bibliographic record

VenueBotany · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
Fundersnot available
KeywordsEcological successionTaigaBorealUnderstoryDisturbance (geology)BiodiversityEcologyAgroforestryOld-growth forestFire regimeGeographyEcosystemBiologyCanopy

Abstract

fetched live from OpenAlex

Boreal forests have commonly been described as dominated by monospecific postfire stands that are reburnt well before other ecological process than those occurring immediately after fire can take place. Research undertaken over the last 30 years has given us a very different perspective of the complexity of Canadian boreal forests. Old-growth forests are common and their development is controlled by nonfire disturbances. Consequently, monospecific even-aged stands can develop towards more diversified uneven-aged stands with increasing time since fire. This complex disturbance regime, including both fire and nonfire disturbances, is partially responsible for a higher than expected biodiversity (e.g., understory) in these forests. The dominating forest management model in Canadian boreal forests, based on clear-cut harvesting and regeneration of short rotation even-aged stands, does not reflect the complexities of the disturbance–succession cycle observed in Canadian natural boreal forests.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.184
Teacher spread0.178 · 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 designObservational
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

Citations130
Published2012
Admission routes3
Has abstractyes

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