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Record W6939302673 · doi:10.60692/e0510-pk325

Respuestas fenológicas de gramíneas C3 y C4 a variaciones interanuales de precipitación y temperatura

2018· article· en· W6939302673 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPhenologyEcosystemPrecipitationClimate changeVegetation (pathology)Range (aeronautics)

Abstract

fetched live from OpenAlex

Temperature and precipitation are key factors in plant phenology and productivity. Modifications on growth and reproductive cycles may affect the relative fitness of the species, altering their interactions and ecosystem functions. In native grasslands of San Luis province, Argentina, C3 (cold-season) and C4 (warm-season) grasses coexist, which makes these grasslands particularly interesting. In this study, we evaluated how phenology of four native grasses (two C3 and two C4) is related to changes in temperature and rainfall. We compared phenological data collected in situ during two periods: from 1976 to 1986 and from 2008 to 2010. We found that warmer summers were related with a delay on the reproductive offset and the length of the reproductive cycle in all four species. In contrast, warmer springs were related with earlier flowering of C4, but later flowering of C3 grasses. Years with rainy winters were related with earlier flowering onsets in C3 species, while rainy summers were related with later and longer reproductive cycles in C4 grasses. These results provide valuable information about vegetation responses to climate and may be used for range management purposes.https://doi.org/10.25260/EA.18.28.2.0.658

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.028
GPT teacher head0.209
Teacher spread0.181 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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