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Record W2171612114 · doi:10.1144/sp381.17

Southern Ocean bioproductivity during the last glacial cycle – new detection method and decadal-scale insight from the Scotia Sea

2013· article· en· W2171612114 on OpenAlexaboutno aff
Daniela Sprenk, Michael E Weber, Gerhard Kühn, P. Rosén, Martin Frank, Mario Molina‐Kescher, Volker Liebetrau, Heinz‐Gerd Röhling

Bibliographic record

VenueGeological Society London Special Publications · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyGlacial periodScale (ratio)OceanographyNova scotiaClimatologyPaleontologyCartographyGeography

Abstract

fetched live from OpenAlex

Abstract We present biogenic opal flux records from two deep-sea sites in the Scotia Sea (MD07-3133 and MD07-3134) at decadal-scale resolution, covering the last glacial cycle. In addition to conventional and time-consuming biogenic opal measuring methods, we introduce new biogenic opal estimation methods derived from sediment colour b *, wet bulk density, Si/Ti-count ratio and Fourier transform infrared spectroscopy (FTIRS). All methods capture the biogenic opal amplitude; however, FTIRS–a novel method for marine sediment – yields the most reliable results. 230 Th normalization data show strong differences in sediment focusing with intensified sediment focusing during glacial times. At MD07-3134 230 Th normalized biogenic opal fluxes vary between 0.2 and 2.5 g cm −2 kyr −1 . Our biogenic opal flux records indicate bioproductivity changes in the Southern Ocean, strongly influenced by sea ice distribution and also summer sea surface temperature changes. South of the Antarctic Polar Front, lowest bioproductivity occurred during the Last Glacial Maximum when upwelling of mid-depth water was reduced and sea ice cover intensified. Around 17 ka, bioproductivity increased abruptly, corresponding to rising atmospheric CO 2 and decreasing seasonal sea ice coverage.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

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

Citations51
Published2013
Admission routes1
Has abstractyes

Explore more

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