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Record W2014630531 · doi:10.7589/0090-3558-41.2.310

SEROLOGIC SURVEY FOR SELECTED VIRUS INFECTIONS IN POLAR BEARS AT SVALBARD

2005· article· en· W2014630531 on OpenAlexaff
Morten Tryland, E. Neuvonen, Anita Huovilainen, Hannele Tapiovaara, Albert D. M. E. Osterhaus, Øystein Wiig, Andrew E. Derocher

Bibliographic record

VenueJournal of Wildlife Diseases · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCalicivirusRabiesFeline calicivirusCanine distemperBiologyVirologyRabies virusMorbillivirusSerologyUrsus maritimusSeroprevalenceVirusCaliciviridaeLyssavirusCarnivoreParamyxoviridaeAntibodyRhabdoviridaeViral diseaseEcologyImmunologyArctic

Abstract

fetched live from OpenAlex

Polar bears (Ursus maritimus) were chemically immobilized and sampled at Svalbard, Norway, and on the pack ice in the Barents Sea from late March to mid-May between 1990 and 1998. Plasma samples were tested for the presence of antibodies to canine distemper virus (CDV), calicivirus, phocid herpesvirus type 1 (PhHV-1), and rabies virus. A seroprevalence of 8% to CDV and 2% to calicivirus were found, whereas no antibodies were detected against PhHV-1 or rabies virus. This serologic survey indicates that polar bears in this region are exposed to morbillivirus and calicivirus, although the nature of these viruses and infections are unknown. Morbillivirus and calicivirus are potential pathogens in seals, but it is unknown whether they may cause health problems in polar bears.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

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 studies0.0010.000
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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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

Citations60
Published2005
Admission routes1
Has abstractyes

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