Derivation of δ<sup>18</sup>O from sediment core log data: Implications for millennial‐scale climate change in the Labrador Sea
Bibliographic record
Abstract
Sediment core logs from six sediment cores in the Labrador Sea show millennial‐scale climate variability during the last glacial by recording all Heinrich events and several major Dansgaard‐Oeschger cycles. The same millennial‐scale climate change is documented for surface water δ18O records of Neogloboquadrina pachyderma (left coiled); hence the surface water δ18O record can be derived from sediment core logging by means of multiple linear regression, providing a paleoclimate proxy record at very high temporal resolution (70 years). For the Labrador Sea, sediment core logs contain important information about deepwater current velocities and also reflect the variable input of ice‐rafted debris from different sources as inferred from grain‐size analysis, the relation of density and P wave velocity, and magnetic susceptibility. For the last glacial, faster deepwater currents, which correspond to highs in sediment physical properties, occurred during iceberg discharge and lasted from several centuries to a few millennia. Those enhanced currents might have contributed to increased production of intermediate waters during times of reduced production of North Atlantic Deep Water. Hudson Strait might have acted as a major supplier of detrital carbonate only during lowered sea level (greater ice extent). During coldest atmospheric temperatures over Greenland, deepwater currents increased during iceberg discharge in the Labrador Sea, then surface water freshened shortly thereafter, while the abrupt atmospheric temperature rise happened after a larger time lag of ≥ 1 kyr. The correlation implies a strong link and common forcing for atmosphere, sea surface, and deep water during the last glacial at millennial timescales but decoupling at orbital timescales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".