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Record W2025291147 · doi:10.1139/x02-053

Croissance juvénile comparée de deux générations successives de semis d'épinette noire issus de graines après feu en forêt boréale, Québec

2002· article· en· W2025291147 on OpenAlexvenueaboutno aff
Natalie Fantin, Hubert Morin

Bibliographic record

VenueCanadian Journal of Forest Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsBlack spruceJuvenileSpruce budwormBiologySeedlingBotanyHorticultureForestryEcologyTaigaGeographyLepidoptera genitaliaTortricidae

Abstract

fetched live from OpenAlex

The objective of this study was to compare juvenile (0–12 years) height growth pattern of dominant mature trees from two virgin black spruce (Picea mariana (Mill.) BSP) forests established during the 19th century (1870) to that of young dominant black spruce seedlings newly regenerated following a 1983 fire on the same sites. The pattern was reconstructed by measuring the distance between terminal bud scars on young seedlings, and by precise counting of growth rings by cross-dating from the collar, which was identified by anatomical features, for mature trees. New seedlings growth was significantly higher than that of mature trees. Seedlings were almost twice as high as mature trees after 12 years of juvenile growth. Assuming that mature trees were dominant during their juvenile growth phase, we put forward the hypothesis that juvenile height growth of mature trees would have been affected by the combined action of spruce budworm (Choristoneura fumiferana (Clem)) and colder climatic conditions than those presently observed. Also, young seedlings juvenile height growth may have been favored by nitrogen soil enrichment along with more favourable climatic conditions.

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 score0.527
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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

Citations11
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicFire effects on ecosystems→French-language works237,207→