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Record W2051633239 · doi:10.1139/z99-250

Causes and consequences of arm damage in the sea star<i>Leptasterias hexactis</i>

2000· article· en· W2051633239 on OpenAlexvenueno aff
Brian L. Bingham, Jennifer Burr, Herb Wounded Head

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBiologyIntertidal zonePopulationPredationEcologyFisheryDemography

Abstract

fetched live from OpenAlex

Leptasterias hexactis, a sea star common in rocky intertidal areas of Puget Sound, Washington, often has damaged or missing arms. We measured the frequency of arm damage in 5 populations and examined the causes and costs of the damage. Between 30 and 46% of L. hexactis found at the study sites were missing arms or parts of arms. Some of the damage, particularly when only parts of arms were missing, may result from physical disturbance (e.g., crushing). Most arm damage, however, appears to result from predation by the crab Cancer oregonensis. The ability to lose, or autotomize, arms has adaptive significance if it saves a sea star from death. However, it also carries costs. The greatest cost was a decrease in reproduction. Leptasterias hexactis missing arms showed a 44-69% drop in egg production 7 months after arm loss. The effect was still evident during the next reproductive season (19 months after arm loss). We estimate that natural levels of arm damage could decrease the reproductive output of a population of L. hexactis by 7-10%.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

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 head0.015
GPT teacher head0.196
Teacher spread0.181 · 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

Citations31
Published2000
Admission routes1
Has abstractyes

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