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Record W1912643297 · doi:10.17770/etr2011vol2.974

The Diversity Of Weeds In Organic Linseed And Flax Crop

2015· article· en· W1912643297 on OpenAlexaboutno aff
Elvyra Gruzdevienė, Z. Jankauskienė

Bibliographic record

VenueEnvironment Technology Resources Proceedings of the International Scientific and Practical Conference · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureFodderLinseed oilLithuanianCropAgroforestryAgronomyAgricultural scienceBusinessBiologyEcologyFood science

Abstract

fetched live from OpenAlex

The flax is grown in the world for many years. The area of linseed in the world is much more than that of fibre flax. The seeds of ecologically grown linseed have high value as the row material for food, medicine, fodder, oil production. The cold pressed oil and seeds of ecologically grown linseed are especially popular in EU, Canada and USA. The quality of the finished linen product is often dependent upon growing conditions and harvesting techniques. The organic textile trend is starting to develop worldwide, while in Lithuania it is still almost non-existent. Therefore, the chance for Lithuanian farmers appears to export the ecological seed and fiber, not only use them in local market. Lithuanian farmers are in luck for the advices how to grow flax in ecological way. Therefore, in 2007- 2009 some investigations were carried out at the Upytė Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry (Panevėžys district, Lithuania). The results of our investigation showed that it is possible to grow and harvest fibre flax and linseed in organic farms without any pesticides. The incidence of weeds is one of the biggest problems in organic growing of flax and linseed.

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 score0.436
Threshold uncertainty score0.336

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.032
GPT teacher head0.221
Teacher spread0.188 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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