MétaCan
Menu
Back to cohort

THE EVALUATION OF GENOTYPE-ENVIRONMENT INTERACTION IN RED BEET VARIETIES OF VIR COLLECTION

2018· article· en· W2903960562 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVEGETABLE CROPS OF RUSSIA · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityYield (engineering)Table (database)AgronomyGeographyBiologyEcologyComputer science

Abstract

fetched live from OpenAlex

The article presents the results of ecological and geographical study of table beet samples of the VIR collection. The study was carried out between 2014 and 2016 in three stations located in different soil and climatic zones of the Russian Federation: in Leningrad, Moscow and Krasnodar regions. The main attention is paid to the interaction of the genotype and the environment, as the main reason for the considerable variability in the yield of table beet varieties when growing them in different ecological and geographical zones. Today the search and creation of an initial high-yielding and versatile material for breeding of adaptive beet varieties is one of the most important trends in the table beet breeding programs. The article describes the evaluation of the factors of time and place of cultivation on yield. The factors that make the greatest contribution in the formation of yield are identified. Significant variability in the yield of collection samples, depending on the cultivation zone, was noted. Samples for the intensive type of cultivation in different zones are identified. The variety of table beet for inclusion in breeding programs, as a source of adaptability and high yield is recommended. The variety of table beet «Perfected Detroid Dark Red» (Canada) is recommended for inclusion in breeding programs as a source of adaptability and high yield.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.151

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 studies0.0000.000
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 head0.031
GPT teacher head0.245
Teacher spread0.214 · 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