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Record W2560734957 · doi:10.1080/11250003.2016.1259360

Age and body size in four introduced populations of the American bullfrog, <i>Lithobates catesbeianus</i> (Ranidae)

2016· article· en· W2560734957 on OpenAlexaffabout
Giulia Tessa, C. Delforno, Purnima Govindarajulu, Nathalie Tissot, Claude Miaud, Franco Andreone

Bibliographic record

VenueItalian Journal of Zoology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsLithobatesBullfrogBiologyPopulationZoologyRange (aeronautics)DemographyNative americanPopulation sizeEcologyEthnology

Abstract

fetched live from OpenAlex

The American bullfrog, native to the eastern half of North America including southern Quebec, is considered one of the most invasive species in the world. It has been introduced in America, Asia and Europe, mainly for food purposes. A study on the age and body size of this species was carried out on individuals obtained from four introduced populations (one from Western Canada and three from France), using the skeletochronological method. Adults did not differ between sexes in mean body size or mean age, with the exception of one population in France where males were younger than females. Several differences in the mean age and body size were observed, with the individuals from the population in Canada exhibiting the highest values for both sexes. The scarcity of studies in the native range prevents the comparison of introduced versus native populations, and we focus on comparisons between introduced populations.

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 score0.153
Threshold uncertainty score0.345

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)0.0000.000

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 head0.011
GPT teacher head0.233
Teacher spread0.221 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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