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Record W1964981192 · doi:10.3201/eid2104.141707

Zika Virus Infection, Philippines, 2012

2015· letter· en· W1964981192 on OpenAlexafffund
Maria Theresa Alera, Laura Hermann, Ilya A. Tac-An, Chonticha Klungthong, Wiriya Rutvisuttinunt, Wudtichai Manasatienkij, Daisy Villa, Butsaya Thaisomboonsuk, John Mark Velasco, Piyawan Chinnawirotpisan, Catherine B. Lago, Vito G. Roque, Louis Macareo, Anon Srikiatkhachorn, Stefan Fernandez, In‐Kyu Yoon

Bibliographic record

VenueEmerging infectious diseases · 2015
Typeletter
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchU.S. Department of Defense
KeywordsZika virusOutbreakFlavivirusVirologyMedicineFlaviviridaeSerologyYellow feverVirusViral diseaseImmunology

Abstract

fetched live from OpenAlex

mammalian adaptation.Various analyses are ongoing to answer questions about the route of transmission among seals and possible transmissibility to humans.Note added in proof: Zohari et al. also recently reported the involvement of avian influenza A(H10N7) virus in mass deaths of harbor seals in Sweden (Euro Surveill.2014;19:pii: 20967).

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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 designCase report
Domainnot available
GenreOther

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

Citations123
Published2015
Admission routes2
Has abstractyes

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