MétaCan
Menu
Back to cohort
Record W1704833857 · doi:10.1371/journal.pone.0116679

Accurate Alternative Measurements for Female Lifetime Reproductive Success in Drosophila melanogaster

2015· article· en· W1704833857 on OpenAlexafffund
Trinh T. X. Nguyen, Amanda J. Moehring

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDrosophila melanogasterBiologyEvolutionary biologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Fitness is an individual's ability to survive and reproduce, and is an important concept in evolutionary biology. However, accurately measuring fitness is often difficult, and appropriate fitness surrogates need to be identified. Lifetime reproductive success, the total progeny an organism can produce in their lifetime, is thought to be a suitable proxy for fitness, but the measure of an organism's reproductive output across a lifetime can be difficult or impossible to obtain. Here we demonstrate that the short-term measure of reproductive success across five days provides a reasonable prediction of an individual's total lifetime reproductive success in Drosophila melanogaster. However, the lifetime reproductive success of a female that has only mated once is not correlated to the lifetime reproductive success of a female that is allowed to mate multiple times, demonstrating that these measures should not serve as surrogates nor be used to make inferences about one another.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.245
GPT teacher head0.294
Teacher spread0.050 · 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

Citations23
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicAnimal Behavior and ReproductionFrench-language works237,207