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Palatability of the Larvae of Three Species of Lithobates

2011· article· en· W1973199886 on OpenAlexafffund
Dorina Szuroczki, Jean M. L. Richardson

Bibliographic record

VenueHerpetologica · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsBrock University
FundersDirectorate for Biological SciencesBrock UniversityOntario Innovation Trust
KeywordsLithobatesPalatabilityPredationBiologyBullfrogLepomisZoologyPredatorLarvaEcologyFood science

Abstract

fetched live from OpenAlex

While unpalatability in general is well-known to provide prey protection against predators, the role of unpalatability as an antipredator mechanism in larval anurans and more specifically, Lithobates catesbeianus (American Bullfrog) larvae remains contentious. There are three major problems associated with the majority of the studies done to date: (1) failure to incorporate the existence of a range of relative preferences or palatability, (2) failure to effectively control for predator hunger levels, and (3) failure to consider confounding variables such as prey behavior and prey appearance. We sought to alleviate these problems by first training Lepomis gibbosus (Pumpkinseed Sunfish) to consume a standardized food ration for 1 wk and then spiking that food ration the following week with only the skin of three different larval anurans that have been hypothesized to range in palatability (namely, L. catesbeianus, L. clamitans [Green Frog], and L. sylvaticus [Wood Frog]). The results of this experiment revealed that a range of palatability does in fact exist, with L. catesbeianus being least palatable, L. clamitans being somewhat unpalatable, and L. sylvaticus being highly palatable. This study was the first to show evidence, devoid of any confounding variables, that L. catesbeianus and, to a lesser extent, L. clamitans tadpoles are unpalatable to sunfish predators.

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 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 score0.054
Threshold uncertainty score0.995

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.042
GPT teacher head0.208
Teacher spread0.166 · 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

Citations15
Published2011
Admission routes2
Has abstractyes

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