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Record W2012421412 · doi:10.5558/tfc82077-1

A characterization of the British Columbia log home and timber frame manufacturing sector

2006· article· en· W2012421412 on OpenAlexaffvenueabout
Paul Thony, Warren Mabee, Robert Kozak, Gary Bull

Bibliographic record

VenueThe Forestry Chronicle · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsWestern Forest ProductsUniversity of British Columbia
Fundersnot available
KeywordsMountain pine beetleManufacturing sectorGeographyOutbreakForestryAgricultural economicsBusinessEconomicsBiology

Abstract

fetched live from OpenAlex

This study characterizes the log home and timber frame manufacturing sector in British Columbia, with a focus on the potential of utilizing insect-killed wood from the mountain pine beetle outbreak. A mail survey was conducted in the spring of 2003 to assess the industry's status. In 2002, an estimated 200 companies were active within BC using approximately 200 000 m3 of fibre, employing 1500 workers, and producing 2200 homes to generate sales of $140 million CDN. Results indicate that these sectors are poised for growth and that firms are willing to using insect-killed wood. Key words: log homes, timber frame homes, industry overview, British Columbia, mountain pine beetle

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)0.000
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 score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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

Citations4
Published2006
Admission routes3
Has abstractyes

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