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Record W2929781676 · doi:10.25260/ea.19.29.1.0.763

Efecto de la disponibilidad de agua sobre una gramínea invasora del caldenal

2019· article· es· W2929781676 on OpenAlexaff
Ruth B. Rauber, Manuel R. Demarı́a, Diego F. Steinaker

Bibliographic record

VenueEcología Austral · 2019
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsBiomass (ecology)IrrigationAridBiologySpring (device)PanicleAgronomyForestryEnvironmental scienceGeographyEcology

Abstract

fetched live from OpenAlex

In the last years, in the semi-arid central region of Argentina, the increase of C3 non-palatable native grass species known generally as “pajas” was observed. One possible cause of the success of these species is the increase in rainfall observed in the region in recent years. The objective of this work was to evaluate the effect of a greater water availability and its seasonal distribution on the biomass and the production of reproductive structures of a non-palatable and highly invasive C3 species (Jarava ichu) and a non-palatable C4 species (Setaria lachnea). For this, a greenhouse experiment was carried out, consisting in manual irrigation of individuals of both species in pots. Treatments were: dry year, wet year with autumnal peak and wet year with spring peak. The increase in water availability favored the biomass of leaves and stems of J. ichu, independently of the seasonal distribution, with respect to the dry year. On the contrary, the biomass of S. lachnea did not respond to the different treatments (P>0.05). Likewise, the number of panicles was greater for J. ichu under the wet year treatment with spring peak, but there were no differences for S. lachnea.https://doi.org/10.25260/EA.19.29.1.0.763

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 score0.066
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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