MétaCan
Menu
Back to cohort
Record W4322746079 · doi:10.1007/978-3-031-15988-6_9

Changes in Water Status and Carbon Allocation in Conifers Subjected to Spruce Budworm Defoliation and Consequences for Tree Mortality and Forest Management

2023· book-chapter· en· W4322746079 on OpenAlexaff
Annie Deslauriers, Lorena Balducci, Angelo Fierravanti, Mathieu Bouchard

Bibliographic record

VenueAdvances in global change research · 2023
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité LavalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsSpruce budwormChoristoneura fumiferanaBalsamBlack spruceTaigaHerbivoreForest managementAgroforestryEcologyForestrySilvicultureBiologyGeographyEnvironmental scienceTortricidaeLepidoptera genitaliaBotany

Abstract

fetched live from OpenAlex

Abstract The ability of forests to provide ecosystem services and renewable goods faces several challenges related to insect defoliation. Spruce budworm outbreaks represent one of the major natural disturbances in the boreal forest of eastern North America. In this chapter, we will focus on the effects of defoliation by eastern spruce budworm in balsam fir and black spruce trees. We first describe tree water status depending on the duration of defoliation. We then present the response of springtime starch reserves and radial growth at different levels of defoliation. We summarize four mechanisms to explain mortality under defoliation and the consequences for forest management.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

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)0.0060.001

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 head0.072
GPT teacher head0.357
Teacher spread0.285 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in global change researchSame topicFire effects on ecosystemsFrench-language works237,207