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Record W2786181085 · doi:10.1139/as-2017-0037

Qualitative risk assessment of impact of Toxoplasma gondii on health of beluga whales, Delphinapterus leucas from the Eastern Beaufort Sea, Northwest Territories

2018· article· en· W2786181085 on OpenAlexaffvenueabout
Rajnish Sharma, Lisa L. Loseto, Sonja Ostertag, Matilde Tomaselli, Christina M. Bredtmann, Colleen Crill, Cristina Rodríguez-Pinacho, Dayna R. Schultz, Dongyun Jung, Kshitiz Shrestha, Prateek Jindal, Emily Jenkins

Bibliographic record

VenueArctic Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of ManitobaFisheries and Oceans CanadaUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsBeluga WhaleBelugaPopulationToxoplasma gondiiGeographyArcticRisk assessmentFisheryEnvironmental healthMarine mammalBiologyEcologyMedicine

Abstract

fetched live from OpenAlex

In recent years, the protozoan parasite Toxoplasma gondii has increasingly been recognized in Arctic fauna, including beluga whales (Delphinapterus leucas) in the Eastern Beaufort Sea (EBS), Northwest Territories. We qualitatively assessed the risks of T. gondii to the health of EBS beluga because of their importance in livelihood of Arctic communities as well as their potential role as sentinels. This risk assessment used a standard framework including hazard identification, hazard characterization, exposure assessment, and risk characterization. We conclude that currently, the EBS beluga are at moderate risk of exposure to T. gondii, and low risk of developing disease associated with toxoplasmosis, based on the small amount of data available (only healthy, hunter-harvested animals have been examined). Although there was a high level of uncertainty due to limited published data and the challenges in determining prevalence and significance of disease in wild marine mammal populations, overall the EBS population was currently considered to be at a low risk for population level impacts of toxoplasmosis. Finally, we identify knowledge gaps that can guide future research, provide better evidence for future risk assessments, and ultimately better detect and mitigate changing risks for health of Arctic beluga, as well as the communities that rely on sustainable, healthy populations for harvest.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.043
GPT teacher head0.388
Teacher spread0.345 · 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

Citations6
Published2018
Admission routes3
Has abstractyes

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