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Record W2257389822 · doi:10.5376/jmr.2016.06.0008

Concurrent Infections of Three Mosquito Borne Diseases-Dengue, Chikungunya and Malaria

2016· article· en· W2257389822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Mosquito Research · 2016
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
Fundersnot available
KeywordsDengue feverChikungunyaVirologyMalariaBiologyMedicineImmunology

Abstract

fetched live from OpenAlex

Kolkata, India is endemic for mosquito borne diseases like dengue, chikungunya and malaria. For monitoring, altogether 252 serum samples of fever cases were examined for dengue specific NS1 antigen and IgM and IgG antibodies and chikungunya specific IgM antibody. Their blood samples were also tested for malarial parasites. Out of 252 cases, 15 (5.95%), 16 (6.34%) and 18 (7.13%) were infected with dengue, chikungunya and malaria respectively. Amongst 15 dengue cases 10 (3.96%) were positive for both dengue IgM and IgG antibodies and 5 (1.98%) for NS1 antigen. Out of 18 malaria victims 14 (5.55%) and 4 (1.58%) were positive for Plasmodium vivax and Plasmodium falciparum respectively. During the present study, one case of concurrent infections of dengue and chikungunya and another case of concurrent infections of dengue, chikungunya and falciparum malaria were detected. Detail case report of the later has been described. This is the first ever report of concurrent infections of dengue, chikungunya and malaria.

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.

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)0.002
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 score0.494
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.377
Teacher spread0.329 · 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