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Record W3039933056 · doi:10.1371/journal.pone.0235285

Spindly leg syndrome in Atelopus varius is linked to environmental calcium and phosphate availability

2020· article· en· W3039933056 on OpenAlexafffund
Elliot Lassiter, Orlando Garcés, Kathleen Higgins, Eric Baitchman, Matthew J. Evans, Jorge Guerrel, Eric Klaphake, Donna Snellgrove, Roberto Ibáñez, Brian Gratwicke

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser University
FundersDirectorate for Biological SciencesFirst Quantum MineralsMorris Animal FoundationSmithsonian InstitutionNational Science Foundation
KeywordsCalciumPhosphateBiologyFactorial experimentAnimal scienceEndocrinologyInternal medicineBiochemistryMedicine

Abstract

fetched live from OpenAlex

Spindly leg syndrome (SLS) is a relatively common musculoskeletal abnormality associated with captive-rearing of amphibians with aquatic larvae. We conducted an experiment to investigate the role of environmental calcium and phosphate in causing SLS in tadpoles. Our 600-tadpole experiment used a fully-factorial design, rearing Atelopus varius tadpoles in water with either high (80mg/l CaCO3), medium (50mg/l CaCO3), or low calcium hardness (20mg/l CaCO3), each was combined with high (1.74 mg/l PO4) or low (0.36 mg/l PO4) phosphate levels. We found that calcium supplementation significantly improved tadpole survival from 19% to 49% and that low calcium treatments had 60% SLS that was reduced to about 15% at the medium and high calcium treatments. Phosphate supplementation significantly reduced SLS prevalence in low calcium treatments. This experimental research clearly links SLS to the calcium: phosphate homeostatic system, but we were unable to completely eliminate the issue, suggesting an interactive role of other unidentified factors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.202
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONE→Same topicFish Ecology and Management Studies→French-language works237,207→