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Record W2048684815 · doi:10.5558/tfc79421-3

Canada's National Forest Inventory: What can it tell us about old growth?

2003· article· en· W2048684815 on OpenAlexaffvenueabout
Mark D. Gillis, Stephen Gray, Dennis Clarke, Katja Power

Bibliographic record

VenueThe Forestry Chronicle · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsCanadian Sport Centre PacificNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsForest inventoryMaturity (psychological)Distribution (mathematics)National forestPerpetual inventoryForest managementInventory managementGeographyEnvironmental resource managementForestryEnvironmental scienceOperations managementEconomicsMathematicsPolitical scienceInventory theory

Abstract

fetched live from OpenAlex

Canada's National Forest Inventory is a periodic compilation of existing inventory information from across the country. The main sources of information are detailed, stand-level descriptions contained in provincial, territorial, and industrial management-level inventories. Typical management inventories do not identify old growth as a specific attribute. Therefore, the National Forest Inventory, based on management-level inventories, does not specifically show old growth. Indicators of old growth, such as stand age and maturity, are contained in the national inventory and are analysed to illustrate the distribution of forest in Canada by age and maturity. A further analysis by selected species is also provided. Finally, a new plot-based national inventory that will provide additional old-growth indicators is discussed. Key words: forest inventory, inventory attributes, old growth, old-growth indicators, NFI, CanFI, EOSD

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.201
Teacher spread0.193 · 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

Citations13
Published2003
Admission routes3
Has abstractyes

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