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Record W2801688740 · doi:10.1139/cjz-2017-0315

Large mothers, but not large fathers, influence offspring number in a caridean shrimp

2018· article· en· W2801688740 on OpenAlexvenueno aff
Daniela Eliana Sganga, Carolina Tropea, Marina Valdora, M.F. Statti, Laura S. López Greco

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersSecretaría de Ciencia y Técnica, Universidad de Buenos AiresAgencia Nacional de Promoción Científica y TecnológicaUniversidad de Buenos AiresConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsOffspringBiologyShrimpSexual maturityGlycogenMaternal effectZoologyEcologyPregnancyEndocrinologyGenetics

Abstract

fetched live from OpenAlex

The relationship between parental mass and female reproductive output, as well as offspring quality, was studied in the red cherry shrimp (Neocaridina davidi (Bouvier, 1904)) under controlled laboratory conditions. Adult males and females of the same age were paired combining different shrimp masses. The number of hatched juveniles from large females was higher than that from small ones, but no influence of paternal mass was detected on this variable. Both the mass of newly hatched juveniles and their growth increment during a 60-day period were similar for all parental masses. Shrimps reached sexual maturity at the end of the growth period in all treatments, and their biochemical reserves (glycogen, lipid, and protein concentrations) were not associated with maternal and paternal masses. However, lipid concentration was higher in female offspring than in male offspring. The present results show that, unlike maternal mass, paternal mass had no effect on female reproductive output and offspring quality, suggesting that the contribution of males to offspring development was adequate regardless of male size.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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