MétaCan
Menu
Back to cohort
Record W4389163527 · doi:10.1139/cjb-2023-0110

Moss regeneration for lithium mine waste rock revegetation in Québec, Canada

2023· article· en· W4389163527 on OpenAlexafffundvenueabout
Chao Liu, Kathy Pouliot, Sébastien Roy, Line Rochefort

Bibliographic record

VenueBotany · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBryophyte Studies and Records
Canadian institutionsUniversité de SherbrookeUniversité LavalCenter for Northern Studies
FundersFonds de recherche du Québec – Nature et technologiesFonds de recherche du Québec
KeywordsRevegetationMossPeatEnvironmental scienceLand reclamationAmendmentEcologyBiology

Abstract

fetched live from OpenAlex

Despite bryophytes being well adapted to various ecological settings, they are rarely considered in reclamation projects. In this study, propagation regenerative capabilities of bryophytes on different substrates (sand, amphibolite, and pegmatite) and conditions (with or without peat amendment, shade and shredding) were tested in greenhouse and field experiments. In the greenhouse trial, after 6 months of reintroduction, Racomitrium species ( Racomitrium canescens (Hedw.) Brid. and Racomitrium elongatum Frisvoll.) had higher regeneration compared to Polytrichum species ( Polytrichum juniperinum Hedw. mixed with Polytrichum piliferum Hedw.; a combination of shade (65% shading) and peat amendment (0.5 cm depth) was found to be particularly effective, resulting in up to 100% of Racomitrium species regeneration; shredding the stems of Polytrichum species into small pieces of 0.5–1.0 cm inhibited its regeneration. In the field trial, peat amendment had no effect on moss regeneration. The addition of fluvioglacial sand or till on waste rocks promoted bryophytes regeneration in both the greenhouse and field. These results provide science-based practical knowledge to support the inclusion of native bryophytes in waste rock restoration plans for mines located in northern boreal forests.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 designNot applicable
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

Citations5
Published2023
Admission routes4
Has abstractyes

Explore more

Same venueBotanySame topicBryophyte Studies and RecordsFrench-language works237,207