Oversampling of sedimentary series collected by giant piston corer: Evidence and corrections based on 3.5‐kHz chirp profiles
Bibliographic record
Abstract
The depth‐scale accuracy of marine sedimentary series collected by coring is of key importance for the precise calculation of sedimentation rates and fluxes. For three giant piston cores collected during the InterPole MD99‐114/International Marine Past Global Changes Study (IMAGES) V cruise (MD99‐2227, MD99‐2246, and MD99‐2251), the 3.5‐kHz chirp profiles recorded on board are compared to synthetic seismograms computed from physical property logs measured on cores. In each case, the perfect match of main deep reflectors requires a significant upward shift of the water‐sediment (W/S) interface in the synthetic seismograms with respect to the 3.5‐kHz profiles. Since no drastic perturbation of the physical property logs is observed, this upward shift is interpreted as resulting from a significant sediment oversampling in the upper part of the cores. The affected depth intervals are consistent with the thickness of the perturbed zones observed in penetrometry and anisotropy of magnetic susceptibility records (∼10–15 m). To retrieve the true in situ sediment thickness, a linear depth correction is applied between consecutive acoustic reflectors to achieve a perfect match between the synthetic seismogram and the corresponding 3.5‐kHz profiles. Depth correction laws (amount of material excess as a function of initial depth) are deduced from this resynchronization procedure. First estimations of upper core oversampling rates range from 30% (core MD99‐2227) to 37% (core MD99‐2246). Moreover, we observe that some undersampling may also exist in the lower part of the sediment cores.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".