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Record W4394463713 · doi:10.6084/m9.figshare.3453380

<sup>40</sup>Ar/<sup>39</sup>Ar hornblende provenance clues about Heinrich event 3 (H3)

2016· dataset· en· W4394463713 on OpenAlexaboutno aff
Greg E. Downing, Sidney R. Hemming, Anne Jost, Martin Roy

Bibliographic record

VenueFigshare · 2016
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsHornblendeProvenanceGeochemistryGeologyEvent (particle physics)MineralogyPhysicsPaleontologyAstrophysicsQuartz

Abstract

fetched live from OpenAlex

Iceberg discharges into the North Atlantic are important sources of fresh water, and the sediments they deposit can provide constraints on which sectors of different ice sheets were contributing icebergs. 40Ar/39Ar ages of sand-sized hornblende grains provide useful constraints on IRD (ice-rafted detritus) source areas. Heinrich events are intervals of anomalously high percentages of IRD in marine sediment cores of the North Atlantic IRD belt. In contrast to the others, Heinrich event 3 (H3) records a significantly lower flux of IRD. This study compares 40Ar/39Ar hornblende age distributions from the interval around and including H3 in giant gravity core EW9303-GGC31 from Orphan Knoll, in the southern part of the Labrador Sea, with piston core V28-82 in the eastern part of the North Atlantic IRD belt. Collectively, these results confirm that H3 represents a Hudson Strait IRD event, but that it was smaller than during H1, H2, H4 and H5, and therefore comprises only a small fraction of the detritus at the eastern North Atlantic location of V28-82. These results support a previously published interpretation of across-strait ice flow during H3 at Hudson Strait.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.266
Teacher spread0.239 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2016
Admission routes1
Has abstractyes

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