MétaCan
Menu
Back to cohort
Record W3081414136 · doi:10.1139/cjfr-2020-0208

The effect of cutting technique on the mortality and resprouting vigor of poplar stumps in short-rotation plantations

2020· article· en· W3081414136 on OpenAlexvenueno aff
Raffaele Spinelli, Natascia Magagnotti, Carolina Lombardini, Elaine Cristina Leonello

Bibliographic record

VenueCanadian Journal of Forest Research · 2020
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsnot available
FundersEuropean Commission
KeywordsCoppicingFellingShootShort rotation forestryShort rotation coppiceBiologyAgroforestryHorticultureWoody plantForestryAgronomyBotanyGeography

Abstract

fetched live from OpenAlex

Mechanical felling is the most cost-effective solution for harvesting short-rotation poplar plantations, but the damage inflicted by conventional shear-cutting devices on tree stumps has raised concerns about stump mortality and resprouting vigor, both of which are crucial to coppice regeneration. To determine whether such concerns are justified, this experiment monitored the survival and resprouting vigor of 11 sample blocks composed of two 10-stump row segments that were cut according to one of two methods: (1) a chainsaw or (2) an excavator-mounted shear. The sample blocks were located within the same plantation, established 7 years earlier with hybrid poplars (Populus nigra × Populus deltoides) belonging to the AF8 clone. One year after cutting, no differences were found between treatments in terms of stump mortality, number of shoots per stump, shoot diameter at 30 cm from the insertion, or shoot height. These results support the use of mechanical shears to fell short-rotation poplar coppice. However, further studies should be conducted on multiple fields and clones in order to safely generalize these preliminary findings.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0000.000

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 head0.067
GPT teacher head0.333
Teacher spread0.266 · 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 teacher head, 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicForest Biomass Utilization and ManagementFrench-language works237,207