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Record W4404693834 · doi:10.3390/d16120719

Temperature Effects on Growth Performance, Fecundity and Survival of Hippocampus guttulatus

2024· article· en· W4404693834 on OpenAlexaff
Jorge Palma, Miguel Correia, Francisco Leitão, José Pedro Andrade

Bibliographic record

VenueDiversity · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsUniversity of British Columbia
FundersFundação para a Ciência e a TecnologiaCentro de Ciências do MarEuropean Commission
KeywordsFecundityBiologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

This experiment aimed to determine the temperature limits beyond which seahorse growth and reproduction become suboptimal due to climate change. Four temperatures (16, 20, 24, and 28 °C) were tested to evaluate their effect on juvenile (1–56 days post-parturition (DPP)) and adult (one year old) long-snout seahorses, Hippocampus guttulatus. Additionally, the reproductive performance of adults was observed. Another experiment measured oxygen consumption (MO2) in the same age groups and temperatures. Adults showed significantly higher growth rates at 20 and 24 °C compared to 16 and 28 °C. Adult mortality rates were 0%, 0%, 6.2%, and 62.5% at the respective temperatures. Juvenile growth performance was higher at 20 °C and 24 °C but significantly lower at 16 °C and null at 28 °C, with survival rates of 8%, 62%, 10%, and 0%, respectively. Oxygen consumption increased with temperature, ranging from 106.3 ± 3.1 to 203.3 ± 3.1 μmol O2/g BW/h at 16 °C, and from 127.6 ± 3.5 to 273.3 ± 3.1 μmol O2/g BW/h at 28 °C for adults and 1 DPP juveniles, respectively. The study highlights that juvenile and adult H. guttulatus have narrow thermal boundaries, beyond which reproduction, growth, and survival are seriously affected. Under climate change, the species appears unable to cope, potentially leading to their rapid disappearance.

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 score0.096
Threshold uncertainty score0.120

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 head0.013
GPT teacher head0.189
Teacher spread0.176 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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