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Environmental aspects of cranberry cultivation in the south of the Khabarovsk Territory

2020· article· en· W3047282034 on OpenAlexaboutno aff
В А Купцова, Т. А. Копотева

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsVacciniumPeatYield (engineering)ShootTea gardenNatural (archaeology)AgroforestryHorticultureValue (mathematics)GeographyBotanyBiologyEcologyMathematicsArchaeologyStatistics

Abstract

fetched live from OpenAlex

Abstract The article represents the results of the introduction of American varieties of Vaccinium macrocarpon in the Khabarovsk Territory. Cranberry is of great value in human nutrition due to its high nutritional significance and unique medicinal value. The experience of plantation cultivation of cranberry in the United States, Canada, Germany, Sweden, Poland, and Belarus proves the high efficiency of its cultivation: yields on plantations are tens or even hundreds of times higher than in natural brushwoods. Early, medium and medium-late varieties with high consumer properties are the most suitable for cultivation in the South of the Khabarovsk Territory. The advantages of cranberry cultivation in the region are the wide distribution of peat-like and peaty soils, suitable natural and climatic conditions, experimental confirmation of the possibility to obtain high yields of berries, and a high economic effect. Cranberry cultivation can also help reduce the anthropogenic load on the natural berry fields of the region. The paper provides data on the survivability, length of shoots growth, and yield of these varieties.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.432

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 studies0.0000.001
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 head0.014
GPT teacher head0.165
Teacher spread0.151 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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