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Record W7112349505

Effects of Temperature and Photoperiod on the Extension Growth of Six Temperate Grasses

2025· article· W7112349505 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsDactylis glomerataphotoperiodismTemperate climateCanopyBromusPastureGrowing seasonPoaceae
DOInot available

Abstract

fetched live from OpenAlex

In western Canada late season pasture yields vary consider­ably among species. During August and early September yields of Bromus riparius and Dactylis glomerata are double that of the more commonly grown Bromus inermis (Knowles and Sonmore, 1985). The importance of leaf area to crop growth rate pnor to canopy closure is well documented (Rhodes, 1973). Two components of leaf area are the final size of leaves and the rate of leaf appearance, with final size of leaves largely dependant on the rate of extension and duration of extension (Edwards, 1967). Since the maturity of a leaf is closely associ­ated with the emergence of a new leaf there is a close associ­ation between rate of appearance and duration of extension (Edwards, 1967). Considerable variation has been shown among and within species for stem extension, leaf extension rate and rate of leaf appearance or duration of extension in response to temperature and photoperiod (Ryle, 1966; Nelson et al., 1978; Heide et al., 1985). Variations among species for late season productivity may be related to the influence of a declining temperature and photoperiod on leaf area and canopy development. The objectives of this study were to examine the extent to which and the mechanisms whereby temperature and photoperiotl affect leaf and stem extension of several grasses commonly grown m western Canada.

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 score0.778
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.175
Teacher spread0.168 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

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