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Record W2089659062 · doi:10.5558/tfc81491-4

Afforestation on private land in Canada from 1990 to 2002 estimated from historical records

2005· article· en· W2089659062 on OpenAlexfundvenueaboutno aff
T. M. White, Werner A. Kurz

Bibliographic record

VenueThe Forestry Chronicle · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersCanadian Forest ServiceMinistry of Natural Resources
KeywordsAfforestationReforestationCarbon sequestrationKyoto ProtocolAgroforestryGeographyForestryEnvironmental scienceClimate changeEcology

Abstract

fetched live from OpenAlex

Information on afforestation on private lands in Canada from 1990 to 2002 was compiled from a variety of sources in support of the Government of Canada's Feasibility Assessment of Afforestation for Carbon Sequestration (FAACS) initiative. Data collection focused on afforestation that was verifiable and consistent with definitions in the Kyoto Protocol. Analysis of the dataset provides insight into the scale, scope and trends in afforestation activity in Canada. Most of the planting occurred in Quebec and Ontario. Ninety-five percent of the afforestation events were smaller than 10 ha. The national average area planted in an afforestation event is 2 ha. Regional averages were higher in the west than in the east. The annual area planted declined from 1990 to 2002 in most provinces, though the Prairie Provinces were an exception. The data agree with other sources of information on afforestation activity in Canada. An analysis of carbon sequestration in the plantations documented in the FAACS database is presently underway and will be reported in the near future. Key words: afforestation, reforestation, climate change, carbon sequestration, Kyoto Protocol, private forest lands

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2005
Admission routes3
Has abstractyes

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