MétaCan
Menu
Back to cohort
Record W4220817415 · doi:10.1080/15230430.2022.2042946

Influence of treatment on rooting of arctic <i>Salix</i> species cuttings for revegetation

2022· article· en· W4220817415 on OpenAlexafffund
Sarah A. Ficko, M. Anne Naeth

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Alberta
FundersWeston Family Foundation
KeywordsCuttingRoot systemRevegetationBiologyTaprootHorticultureGrowing seasonShrubBotanyAgronomyEcological succession

Abstract

fetched live from OpenAlex

Increased northern exploration and resource extraction highlight a need for effective revegetation techniques to restore disturbed environments. This study assessed effects of indole-3-butyric acid (IBA), water extracts of Salix and smoke, soaking time, and collection time on adventitious and lateral root development of Salix species cuttings collected from Diavik Diamond Mine Inc., Northwest Territories. Over 80 percent of fall and spring cuttings developed adventitious roots, yet only 30 percent of summer cuttings rooted, indicating strong seasonal influences. Many cuttings developed extensive root system architecture in 60 days; some developed up to six orders of roots. Root length decreased with increasing root order in all seasons, and season influenced length within root orders. Application of IBA increased number of primary roots per cutting per season and number of cuttings with less than fifty secondary roots per primary root. Longer soaking times increased number of primary roots per cutting in different seasons, and soaking up to ten days increased longest root length. Salix and smoke water extract applications increased number of cuttings with twenty-five to seventy-four secondary roots. This research highlights the importance of treatment effects on adventitious and lateral root development to optimize root system architecture of cuttings from northern shrub species.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.312
Teacher spread0.256 · 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 designBench or experimental
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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueArctic Antarctic and Alpine ResearchSame topicPlant Molecular Biology ResearchFrench-language works237,207