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Record W1974184543 · doi:10.1111/btp.12118

Morphology, Diet and Flower‐visiting by Phyllostomid Bats in Cuba

2014· article· en· W1974184543 on OpenAlexafffund
Lindsey Clairmont, Emanuel C. Mora, M. Brock Fenton

Bibliographic record

VenueBiotropica · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsWestern University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsPollinatorBiologyFrugivoreMorphology (biology)PollinationLimitingHuman echolocationEcologyPollenZoologyBotany

Abstract

fetched live from OpenAlex

Abstract Pollinator morphology can play an important role in structuring plant–pollinator relationships and a pollinator's morphology may be associated with aspects of its diet. We examined the relationship between morphology and the partitioning of flower‐based food resources for five species of flower‐visiting Cuban bats: A rtibeus jamaicensis , B rachyphylla nana , E rophylla sezekorni , M onophyllus redmani and P hyllonycteris poeyi . We analyzed cranial traits and body size to assess differences among species with respect to morphological specializations. We also collected dietary data from guano and used acoustic monitoring to assess bat activity at flowers. We found evidence that bats partition floral resources, but we found no direct evidence that plants were limiting resources for the bats. Morphological similarity among bat species did not predict dietary overlap. Rather it was associated with phylogenic relationships among some species. Species with different morphological specialization for flower‐visiting consumed resources and visited food plants at different frequencies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.166

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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

Citations12
Published2014
Admission routes2
Has abstractyes

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