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Record W2566448187 · doi:10.1093/jmedent/45.5.841

Species Composition and Distribution of Adult<i>Anopheles</i>(Diptera: Culicidae) in Panama

2008· article· en· W2566448187 on OpenAlexaff
José R. Loaiza, E. Bermingham, Marilyn E. Scott, José R. Rovira, Jan E. Conn

Bibliographic record

VenueJournal of Medical Entomology · 2008
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsMcGill University
FundersSmithsonian Institution
KeywordsAnopheles albimanusAnophelesBiologyMalariaVector (molecular biology)PanamaZoologyEcologyVeterinary medicine

Abstract

fetched live from OpenAlex

Anopheles (Diptera: Culicidae) species composition and distribution were studied using human landing catch data over a 35-yr period in Panama. Mosquitoes were collected from 77 sites during 228 field trips carried out by members of the National Malaria Eradication Service. Fourteen Anopheles species were identified. The highest average human biting rates were recorded from Anopheles (Nyssorhynchus) albimanus (Wiedemann) (9.8 bites/person/night) and Anopheles (Anopheles) punctimacula (Dyar and Knab) (6.2 bites/person/night). These two species were also the most common, present in 99.1 and 74.9%, respectively, of the sites. Anopheles (Nyssorhynchus) aquasalis (Curry) was encountered mostly in the indigenous Kuna Yala Comarca along the eastern Atlantic coast, where malaria case history and average human biting rate (9.3 bites/person/night) suggest a local role in malaria transmission. An. albimanus, An. punctimacula, and Anopheles (Anopheles) vestitipennis (Dyar and Knab) were more abundant during the rainy season (May-December), whereas An. aquasalis was more abundant in the dry season (January-April). Other vector species collected in this study were Anopheles (Kerteszia) neivai (Howard, Dyar, and Knab) and Anopheles (Anopheles) pseudopunctipennis s.l. (Theobald). High diversity of Anopheles species and six confirmed malaria vectors in endemic areas of Panama emphasize the need for more detailed studies to better understand malaria transmission dynamics.

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)0.000
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 score0.071
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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

Citations48
Published2008
Admission routes1
Has abstractyes

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