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Record W1979969848 · doi:10.1139/f09-187

Ontogenetic changes in the feeding habits of the abalone Haliotis discus hannai: field verification by stable isotope analyses

2010· article· en· W1979969848 on OpenAlexvenueno aff
Nam‐Il Won, Tomohiko Kawamura, Hideki Takami, TADAKATSU NORO, Tatsuya Musashi, Yoshirô Watanabe

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersUniversity of TokyoCERN
KeywordsAbaloneHaliotis discusJuvenileBiologyOntogenyZoologyStable isotope ratioEcologyAnimal scienceFishery

Abstract

fetched live from OpenAlex

The ontogenetic changes in the feeding habits of the abalone Haliotis discus hannai were elucidated for the first time in natural habitats using stable isotope analyses. Abalone individuals were grouped into three developmental stages: small juveniles (<10 mm shell length (SL)), large juveniles (10–50 mm SL), and adults (>50 mm SL). The inferences of natural diets indicated that benthic diatoms, small red macroalgae and (or) juvenile brown macroalgae, and adult brown macroalgae were the primary food sources for small juveniles (6.5 ± 1.0 mm SL), large juveniles (23.7 ± 6.1 mm SL), and adults (81.8 ± 14.3 mm SL), respectively. The changes of δ13C in abalone were similar among three sampling stations and were explained by ontogenetic changes in feeding habits. The decrease of δ13C in abalone (≤20 mm SL) indicated a transition from diatom feeding to juvenile brown macroalgae and (or) small red macroalgae feeding, whereas the subsequent increase of δ13C (>20 mm SL) represented a feeding transition to adult brown macroalgae. These results prove the hypothesis of the ontogenetic changes in the feeding habits of the abalone H. discus hannai.

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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.246
Teacher spread0.225 · 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

Citations28
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207