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Record W2236025997 · doi:10.1139/cjfr-2015-0355

Responses of Norway spruce seedlings to different night interruption treatments in autumn

2016· article· en· W2236025997 on OpenAlexvenueno aff
Johanna Riikonen, Juha Lappi

Bibliographic record

VenueCanadian Journal of Forest Research · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsnot available
FundersEuropean Social Fund
KeywordsPicea abiesHorticultureShootPhotosynthetically active radiationFrost (temperature)Growing seasonBotanyAnimal scienceAnnual growth cycle of grapevinesBiologyPhotosynthesisGeographyMeteorology

Abstract

fetched live from OpenAlex

Photoperiodic lighting can be used in late summer to prevent height growth cessation and terminal bud formation in nurseries growing forest tree species in Nordic countries. To create guidelines for using the method in container nurseries growing Norway spruce (Picea abies (L.) Karst.) and to test the use of light-emitting diode (LED) technology, we exposed first-year, nursery grown seedlings to the following night interruption (NI) treatments from 10 July 2014 onwards (00:00–03:00): (i) no lighting, (ii) 1 min lighting at intervals of 30 min, (iii) 1 min lighting at intervals of 15 min, and (iv) 3 h continuous lighting. Light intensities (LI) of 10, 25, and 70 μmol photosynthetically active radiation (PAR) m −2 ·s −1 were used. Growth, formation of terminal buds, and winter damage of the seedlings were measured. All NI treatments prevented growth cessation at LI of 25 and 70 μmol PAR·m −2 ·s −1 , but the intermittent treatments were less effective at a LI of 10 μmol PAR·m −2 ·s −1 . The treatments of duration longer than 1 min at intervals of 30 min did not provide any additional increase in shoot growth but predisposed the seedlings to frost injury during autumn and winter. Both seed origins used in this experiment responded similarly to the NI treatments.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.074
GPT teacher head0.323
Teacher spread0.249 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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