MétaCan
Menu
Back to cohort
Record W2135988999 · doi:10.5558/tfc78306-2

Height growth of black spruce in British Columbia

2002· article· en· W2135988999 on OpenAlexafffundvenueabout
Gordon D. Nigh, Pavel V. Krestov, Karel Klinka

Bibliographic record

VenueThe Forestry Chronicle · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of British ColumbiaGovernment of British Columbia
FundersU.S. Forest ServiceUniversity of British Columbia
KeywordsBlack spruceSite indexForestryGeographyBorealTaigaEnvironmental scienceEcologyPhysical geographyBiologyArchaeology

Abstract

fetched live from OpenAlex

Black spruce (Picea mariana (Mill.) B.S.P.) is a boreal species that occurs extensively across the northern half of British Columbia. Forest managers require better growth and yield information for black spruce given the anticipated increase in demand for wood in the northern part of the province. The purpose of this study was to develop height-age models for black spruce. Ninety-one stem analysis plots were established in the BWBS and SBS biogeoclimatic zones. Three black spruce site trees from each plot were stem analyzed and the data were converted into height-age data. A conditioned log-logistic function was fit to the data. Indicator variables were used to test for differences in height growth between the sampled subzones. Although the warm subzones had different height growth patterns than the cool subzones, there was general agreement among the height-age models from British Columbia, Alberta, and New Brunswick up to about age 100. Key words: biogeoclimatic zones, height-age models, logistic function, site index, stem analysis

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 score0.107
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.185
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

Citations9
Published2002
Admission routes4
Has abstractyes

Explore more

Same venueThe Forestry ChronicleSame topicForest ecology and managementFrench-language works237,207