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Record W4214863235 · doi:10.3934/mbe.2022203

Temperature dependent developmental time for the larva stage of Aedes aegypti

2022· article· en· W4214863235 on OpenAlexaff
Meili Li, Rongrong Guo, Wei Ding, Junling Ma

Bibliographic record

VenueMathematical Biosciences & Engineering · 2022
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPupaLarvaAedes aegyptiBiologyDevelopmental stageStage (stratigraphy)StatisticsMathematicsEcology

Abstract

fetched live from OpenAlex

We first verify that the time from the emergence of larva to the emergence of pupa (i.e., the duration of the larva stage) for Aedes aegypti is approximately gamma distributed, provided that the pupation process is successful. This is illustrated by fitting a multi-stage model to temperature-controlled pupation rate data of Aedes aegypti. We then determine the temperature dependent gamma distribution parameters, and found that both the shape and rate parameters and the survival probability are unimodal functions of temperature. We then use a Gaussian unimodal function to describe the dependence of these parameters on temperature, and fit the model to the pupation rate data. We found that the optimal pupation temperature is about 28℃, with a mean time from the emergence of larva to the emergence of pupa about 3.8 days, and standard deviation of 0.5 days. For very high and very low temperatures, the death rate is 1.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.904

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)0.0010.000

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 head0.009
GPT teacher head0.232
Teacher spread0.222 · 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 designBench or experimental
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

Citations5
Published2022
Admission routes1
Has abstractyes

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