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Record W2479621539 · doi:10.1016/s0967-0653(97)81190-8

10.1016/s0967-0653(97)81190-8

2000· article· en· W2479621539 on OpenAlexvenueno aff
JB Hulscher, D Alting, E.J. Bunskoeke, B.J. Ens, Dik Heg

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsMacoma balthicaBiologyZoologyEcologyBivalviaMollusca

Abstract

fetched live from OpenAlex

In this paper an analysis is made of subtle behavioural differences between adult male and female Ovstercatchers feeding on Macoma balthica under field conditions and in captivity. Macoma is a tellinid bivalve that in the Dutch Wadden Sea is mainly preyed upon during spring and summer when it is buried at a shallow depth. males lift Macoma more, whereas females handle them mostly in situ. Both sexes handle a Macoma in situ faster than one lifted. Time loss of males in handling more lifted Macoma is compensated by the larger size of lifted Macoma, which yields more flesh. The time the birds need to find an edible Macoma is similar for both sexes, resulting in equal mean food intake rates for males and females in the field. Lifted Macoma are generally hammered and, since males with their short strong bills are more likely to hammer bivalves than females, this difference in bill morphology might explain why males more often lift Macoma than do females, especially as hammering produces a blunt bill tip which would reduce efficiency at opening Macoma in situ. However, none of the selected bill morphology variables showed a relationship within the sexes that explained the differences between the sexes.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.006
Open science0.0030.004
Research integrity0.0060.002
Insufficient payload (model declined to judge)0.9850.985

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 head0.008
GPT teacher head0.185
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2000
Admission routes1
Has abstractyes

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