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Record W4406126708 · doi:10.1080/15376516.2024.2449417

Development of a gradual hypoxia chamber for assessing copper toxicity on air-breathing behavior in <i>Lymnaea stagnalis</i>

2025· article· en· W4406126708 on OpenAlexafffund
Lauren Zink, Chris M. Wood

Bibliographic record

VenueToxicology Mechanisms and Methods · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLymnaea stagnalisHypoxia (environmental)LymnaeaRespirationToxicologyBiologyBreathing gasAcclimatizationSnailEcologyOxygenEnvironmental chemistryBreathingChemistryBotanyAnatomy

Abstract

fetched live from OpenAlex

. Studies assessing the switch from water- to air-breathing in hypoxic conditions have previously utilized methods that neglect intricacies of animal behavior such as handling stress and acclimation. The chamber provides a linear decline in dissolved oxygen, against which surfacing behavior for air-breathing can be precisely measured. The maximum biomass of snails suitable for use in the hypoxia chamber, such that the nitrogen-driven deoxygenation curve is not altered by the snails' own metabolism, was established to be greater than 10 adult snails. The capacity of most analysis softwares is below accurately tracking 10 individuals at once, indicating this is likely not a limitation. The size of snails determined the amount of time each episode of aerial respiration was, with smaller snails spending more time air-breathing. A proof-of-principle experiment using acute copper exposure (0 - 60 µg/L) yielded a concentration-response curve, with greater copper concentrations inhibiting air-breathing. The chamber described in the present study provides an improved framework for assessing hypoxic response and is presented in a manner allowing for further modification to meet unique research needs.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.457
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.352
Teacher spread0.320 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes2
Has abstractyes

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