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Record W4362470173 · doi:10.3389/fvets.2023.1040125

Pinniped electroencephalography: Methodology and findings in California sea lions (Zalophus californianus)

2023· article· en· W4362470173 on OpenAlexaff
D. Colette Williams, Martin Haulena, Sophie Dennison, Lynnette Waugh, Tracey Goldstein, Felicia B. Nutter, Vanessa Hoard, Kenneth D. Laxer, Paul S. Buckmaster, Frances M. D. Gulland, Barry R. Tharp

Bibliographic record

VenueFrontiers in Veterinary Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsVancouver Aquarium
FundersNational Institute of Environmental Health SciencesNational Institute of Neurological Disorders and StrokeNihon Kohden America
KeywordsZalophus californianusSea lionElectroencephalographyFisheryGeographyBiologyNeuroscience

Abstract

fetched live from OpenAlex

. Recordings from animals presenting for non-neurological issues were also obtained to better understand the normal EEG (background activity and transient events) in this species, as, to date, studies have focused on examining natural sleep in pinnipeds. Most animals were sedated for electrode placement and EEG acquisition with some receiving antiepileptic medications or isoflurane during the procedure. A total of 103 recordings were read and scored from 0 (normal) to 3 (severely abnormal). Epileptiform discharges, consisting of spikes, sharp waves, slow waves, and/or spike waves, were present in all EEGs with scores of 1, 2, or 3. The distribution of these events over the scalp varied. While often generalized, others were lateralized over one hemisphere, bifrontal, bioccipital, and/or bitemporal, while some discharges were multifocal. Findings were different between sea lions and occasionally changed within the EEG on a given sea lion. No clinical seizures were observed during the recording but a few sea lions had findings consistent with electroencephalographic seizures. When available, supporting diagnostic results obtained from magnetic resonance imaging (MRI) and/or necropsy/histopathology were described, as well as the status of those sea lions that recovered and were released with satellite tags.

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)0.003
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 score0.123
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.034
GPT teacher head0.303
Teacher spread0.269 · 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
Published2023
Admission routes1
Has abstractyes

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