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Record W2177965155 · doi:10.1139/f04-009

Radiocarbon in otoliths of yelloweye rockfish (<i>Sebastes ruberrimus</i>): a reference time series for the coastal waters of southeast Alaska

2004· article· en· W2177965155 on OpenAlexvenueno aff
Lisa A. Kerr, Allen H. Andrews, Brian R. Frantz, Kenneth H. Coale, Thomas A. Brown, Gregor M. Cailliet

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsRockfishSebastesRadiocarbon datingOceanographyScorpaenidaeFisheryEnvironmental scienceGeologySeawaterBefore PresentOtolithFish <Actinopterygii>BiologyPaleontologyHolocene

Abstract

fetched live from OpenAlex

Atmospheric testing of thermonuclear devices during the 1950s and 1960s created a global radiocarbon ( 14 C) signal that has provided a useful tracer and chronological marker in oceanic systems and organisms. The bomb-generated 14 C signal retained in fish otoliths can be used as a time-specific recorder of the 14 C present in ambient seawater, making it a useful tool in age validation of fishes. The goal of this study was to determine 14 C in otoliths of the age-validated yelloweye rockfish (Sebastes ruberrimus) to establish a reference time series for the coastal waters of southeast Alaska. Radiocarbon values from the first year's growth of 43 yelloweye rockfish otoliths plotted against estimated birth year produced a 14 C time series (1940–1990) for these waters. The initial rise of 14 C occurred in 1958 and 14 C levels rose to peak values (60–70‰) between 1966 and 1971, with a subsequent declining trend through the end of the record in 1990 (–3.2‰). In addition, the 14 C data confirmed the longevity of the yelloweye rockfish to a minimum of 44 years and strongly support higher age estimates. This 14 C time series will be useful for the interpretation of 14 C accreted in biological samples from these waters.

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)0.001
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 score0.135
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.010
GPT teacher head0.196
Teacher spread0.187 · 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

Citations58
Published2004
Admission routes1
Has abstractyes

Explore more

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