MétaCan
Menu
Back to cohort
Record W4386069914 · doi:10.3390/f14091693

The Production Chain of Tree Seedlings, from Seeds to Sustainable Plantations: An Essential Link for the Success of Reforestation and Restoration Programs in the Context of Climate Change

2023· article· en· W4386069914 on OpenAlexaff
Mohammed S. Lamhamedi, Steeve Pépin, Damase P. Khasa

Bibliographic record

VenueForests · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversité LavalMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsReforestationAgroforestryContext (archaeology)AfforestationTree plantingForest restorationSeedlingClimate changeProduction (economics)SowingForestryForest managementEnvironmental scienceGeographyForest ecologyBiologyAgronomyEcologyEcosystem

Abstract

fetched live from OpenAlex

Although the evolution of principles, procedures, and predictive abilities related to seedling quality throughout the plant production chain (i.e., from seeds to sustainable plantations) has been reviewed over the past decades in various technical and scientific publications, there is still a need to develop and integrate new and efficient practices in forest nurseries and at planting sites, in order to improve the morphophysiological quality of seedlings and saplings, and their survival and growth under different site and environmental conditions in the context of climate change. We have grouped together different scientific articles in this Special Issue of Forests, entitled “Production in Forest Nurseries and Field Performance of Seedlings”. They cover different topics relating to the seedling production chain in different countries and continents, from growing media to planting performance related to reforestation, restoration, and agroforestry programs.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.101
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.033
GPT teacher head0.280
Teacher spread0.246 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueForestsSame topicSeedling growth and survival studiesFrench-language works237,207