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Record W7119005499 · doi:10.26480/asm.01.2025.13.18

A MORPHOLOGICAL STUDY OF Leptoconops spinosifrons (DIPTERA: CERATOPOGONIDAE) AT BAGAN LALANG BEACH, SELANGOR

2025· article· W7119005499 on OpenAlexaboutno aff
Nur Amalina Kamarudin, Mohd Khadri Shahar, Nur Afrina Muhamad Hendri

Bibliographic record

VenueActa Scientifica Malaysia · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxonomy (biology)TourismCamouflageBalsam

Abstract

fetched live from OpenAlex

Leptoconops are tiny blood-feeding insects commonly found in sandy beaches of tropical and sub-tropical regions and is known for its irritating bites. Their bites can cause allergic reactions and scarring. Leptoconops spinosifrons were collected from Bagan Lalang beach in Selangor with human landing catch (HLC) and modified emergence traps techniques. The specimens collected were mounted on microscope slides in Canada Balsam for morphological identification. The basic morphological features of L. spinosifrons were based on taxonomy key. In addition, the morphological features of male and female L. spinosifrons were differentiated in this study. This study aimed to describe the morphological characteristics of L. spinosifrons. The morphological characteristics of the poorly-known L. spinosifrons in this study are the first reported in Malaysia. It provides crucial surveillance data for this medically important, yet neglected insect that is associated with outdoor and tourism activities.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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