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Record W3005975124 · doi:10.1071/mf19280

Age validation of four rockfishes (genera Sebastes and Sebastolobus) with bomb-produced radiocarbon

2020· article· en· W3005975124 on OpenAlexaff
Craig R. Kastelle, Thomas E. Helser, Todd T. TenBrink, Charles Hutchinson, Betty J. Goetz, Chris Gburski, Irina M. Benson

Bibliographic record

VenueMarine and Freshwater Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsRockfishSebastesScorpaenidaeOtolithHalibutFisheryBiologyRadiocarbon datingElectrofishingEcologyOceanographyGeologyFish <Actinopterygii>Paleontology

Abstract

fetched live from OpenAlex

In rockfish (Family Scorpaenidae), age determination is difficult and the annual nature of otolith growth zones must be validated independently. We applied routine age determination to four species of Gulf of Alaska rockfish: two shallower-water species, namely harlequin rockfish (Sebastes variegatus) and redstripe rockfish (Sebastes proriger), and two deep-water species, namely shortspine thornyhead (Sebastolobus alascanus) and shortraker rockfish (Sebastes borealis). The estimated ages (counts of presumed annual growth zones in the otoliths) were then evaluated with bomb-produced radiocarbon (14C) and Bayesian modelling with Markov chain Monte Carlo simulations. This study successfully demonstrated the level of accuracy in estimated ages of redstripe rockfish (a 35% probability of underageing, and ~5% probability of overageing) and harlequin rockfish (a 100% probability that they were underaged by ~3 or 4 years). Measured Δ14C in shortspine thornyhead and shortraker rockfish otoliths was lower and increased later than expected. Hence, incorrect age determination could not be evaluated. This is likely caused by dissimilar environmental and biological availability of 14C between these two species and the Pacific halibut (Hippoglossus stenolepis) reference chronology, or underageing of these two species.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.263
Teacher spread0.204 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

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