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Record W4249604446 · doi:10.24124/2009/bpgub648

Geographic variation in the effect of lodgepole pine characteristics on mountain pine beetle attacks and productivity in British Columbia.

2009· dissertation· en· W4249604446 on OpenAlexaboutno aff
Timothy J. Cudmore

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPinus contortaMountain pine beetleDendroctonusCurculionidaeProductivityForestryGeographyEcologyBark beetleBiology

Abstract

fetched live from OpenAlex

The mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae: Scolytinae), is the most destructive bark beetle in mature lodgepole pine (Pinus contorta Dougl. Ex Loud.var. latifolia Engelm.) forests in western Canada... The current outbreak in British Columbia is the largest in recorded history... Host factors and historic climate affecting attack dynamics and pupal chamber productivity of MPB on lodgepole pine were examined in southern and north central BC. Trees were felled and intensively sampled in fourteen pine-leading stands. A between-subjects two-by-two factorial ANOVA was conducted to analyze the effects of historic climate and biogeoclimatic subzone on MPB attack and productivity parameters. The effect of dbh on mean gallery start densities was not different between regions, while mean pupal chamber density was significantly higher in areas of historically low climatic suitability than in areas with historically high climatic suitability. Results indicate that north central trees are more suitable for pupal chamber production than southern. Lack of selection pressure in areas of low climatic suitability for mountain pine beetle may be the explanation for this relationship.

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 score0.127
Threshold uncertainty score0.255

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 science0.0000.000
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 head0.003
GPT teacher head0.208
Teacher spread0.206 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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