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Record W2796018019 · doi:10.1139/cjb-2017-0232

Germination response of <i>Lithraea molleoides</i> seeds is similar after passage through the guts of several avian and a single mammalian disperser

2018· article· en· W2796018019 on OpenAlexvenueno aff
David L. Vergara‐Tabares, Juan I. Whitworth‐Hulse, Guillermo Funes

Bibliographic record

VenueBotany · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsFrugivoreGerminationBiologySeed dispersalSeed predationSeed dispersal syndromeBiological dispersalEcologyBotanyPopulationHerbivorePredationHabitat

Abstract

fetched live from OpenAlex

Seed dispersal by vertebrate frugivores plays an important role in plant population dynamics and community structure. The gut treatment may modify the germination response of seeds; often the specific effects of seed ingestion are not consistent among frugivorous taxa. In the Chaco mountain woodlands of Argentina, an ecosystem threatened by human activities, frugivorous birds enhance the seed germination of the most abundant fleshy-fruited plants. However, the effect of the identity of dispersers on seed germination remains unknown. In this work, we evaluated and compared the seed germination response of Lithraea molleoides (Vell.) Engl. (the dominant tree of the region) to gut passage through three Turdus species and the Pampa Fox (Lycalopex gimnocercus). Owing to anatomical differences between the Turdus species and Pampa Fox, we expected to observe higher seed germination in the seeds treated by the gut of Turdus species compared with those that have passed through the Pampa Fox’s gut. Our results showed that germination response of L. molleoides seeds was positively related to gut passage through Turdus species and Pampa Foxes (without differences among seed dispersers). Consequently, both the avian species and the Pampa Fox contribute positively to the dispersal and germination of L. molleoides seeds.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.126

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 head0.025
GPT teacher head0.220
Teacher spread0.194 · 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 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

Citations11
Published2018
Admission routes1
Has abstractyes

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