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Record W1992390029 · doi:10.1097/hp.0b013e3181aadce1

ESR DATING PLEISTOCENE BARNACLES FROM BC AND MAINE: A NEW METHOD FOR TRACKING SEA LEVEL CHANGE

2010· article· en· W1992390029 on OpenAlexaff
Bonnie A.B. Blackwell, J. Gong, Anne R. Skinner, A Blais-Stevens, Robert E. Nelson, Joel I.B. Blickstein

Bibliographic record

VenueHealth Physics · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsBarnacleBalanusGeologyOceanographyIntertidal zoneSea levelSedimentPaleontologyCrustaceanEcologyBiology

Abstract

fetched live from OpenAlex

Barnacles have never been successfully dated by electron spin resonance (ESR). Living mainly in the intertidal zone, barnacles die when sea level changes cause their permanent exposure. Thus, dating the barnacles dates past sea level changes. From this, we can measure apparent sea level changes that occur due to ocean volume changes, crustal isostasy, and tectonics. ESR can date aragonitic mollusc shells ranging in age from 5 ka to at least 500 ka. By modifying the standard ESR method for molluscs to chemically dissolve 20 microm from off the shells, six barnacle samples from Norridgewock, Maine, and Khyex River, British Columbia, were tested for suitability for ESR dating. Due to Mn2+ interference peaks, the four Maine barnacle samples were not datable by ESR. Two barnacles from BC, which lacked Mn2+ interference, yielded a mean ESR age of 15.1 +/- 1.0 ka. These ages agree well with 14C dates on the barnacles themselves and wood in the overlying glaciomarine sediment. Although stability tests to calculate the mean dating signal lifetime and more ESR calibration tests against other barnacles of known age are needed to ensure the method's accuracy, ESR can indeed date Balanus, and thus, sea level changes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.169
GPT teacher head0.385
Teacher spread0.216 · 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 designBench or experimental
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

Citations13
Published2010
Admission routes1
Has abstractyes

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