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Record W3110912655 · doi:10.1139/cjfas-2020-0327

Impacts of water temperature on the physiology and behaviours of the sea urchins <i>Heliocidaris crassispina</i> and <i>Mesocentrotus nudus</i> that reflect their range extension and disappearance in the Oga Peninsula, northern Honshu, Japan

2020· article· en· W3110912655 on OpenAlexvenueno aff
Wenping Feng, Nobuyasu Nakabayashi, Eri Inomata, Masakazu Aoki, Yukio Agatsuma

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyEcologyZoologyEffects of global warming on oceansGlobal warmingClimate change

Abstract

fetched live from OpenAlex

Ocean warming has facilitated the extension of Heliocidaris crassispina to Oga Peninsula, Japan, where the native species Mesocentrotus nudus has disappeared. To verify the temperature impacts on the physiology and behaviour of the two species, we reared small sea urchins at the increasing–decreasing temperature rate of 2.5 °C·week−1. The righting response, lantern reflex, gonad and gut carbon (C) and nitrogen (N) contents, and feeding rate were investigated. The high and low temperature limits of H. crassispina were 33.3 and 3.9 °C, respectively, which were higher than those of M. nudus. The optimal temperature ranges for behaviour and feeding in H. crassispina were 10.3–31.0 and 10.3–33.4 °C, respectively, which were higher than those in M. nudus. Feeding rates decreased significantly in both species when the temperature approached the high or low temperature limit, but the gut C and N contents of were not greatly affected. At 26–31 °C, the feeding rate significantly decreased in M. nudus but not in H. crassispina, which may explain the replacement of M. nudus by H. crassispina in the Oga Peninsula.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.192
Teacher spread0.173 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

Explore more

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