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Barley and wheat under controlled climatic conditions: A model experiment of vigour and variability

2008· article· en· W1974722843 on OpenAlexaff
Åke Gustafsson, Ingegerd Dormling, Gunnar Ekman

Bibliographic record

VenueHereditas · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsInstitute of Genetics
Fundersnot available
KeywordsPhytotronBiologyAgronomyGrain yieldYield (engineering)Spring (device)ProductivityEngineering

Abstract

fetched live from OpenAlex

Two cereal varieties (Bonus spring barley and Drabant spring wheat) were cultivated in the Stockholm phytotron according to standard methods previously described. Bonus is more long-day adapted and more specialized than Drabant, both generatively and vegetatively. Drabant does not reach the maximal level of grain productivity found in Bonus. This variety, however, when compared to Drabant, is characterized by an evident “waste” of vegetative matter for each unit of grain weight produced. Drabant, although lower in maximal yield, shows a higher generative efficiency, especially at shortened day lengths and raised temperatures. Phene variability is rather similar in the two varieties, with some striking exceptions, however. Different degrees of variability are apparently built into the individual traits (phenes) of which the barley plant, or the wheat plant, is composed, reacting in specific ways to the different kinds of phytotron environment.

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 score0.934
Threshold uncertainty score0.173

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 studies0.0000.000
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 head0.030
GPT teacher head0.242
Teacher spread0.212 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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