Astronomical climate forcing and tuning of the Baringo core (HSPDP-BTB13-1A), Kenya
Bibliographic record
Abstract
The core from the Baringo-Tugen Hills-Barsemoi paleolake area in Kenya (called BTB13) provides an excellent opportunity to study east African hydroclimate in relation to human evolution and global climate change during the Pliocene-Pleistocene transition. As age control is critical, a Bayesian age model was previously constructed based on magnetostratigraphy and radio-isotopic dating. In order to improve the existing age model, we astronomically-tune the BTB13 core using the available gamma density and magnetic susceptibility records. Spectral analysis and bandpass filtering revealed a dominance of obliquity-related variability, which was used to establish an initial tuning. Significant precession-related variability was subsequently used to tune the records to precession and a standardized obliquity-precession target curve. The precession-paced variability is in very good agreement with precession-obliquity interference, making a shift in the tuning unlikely. Deep lake phases, characterized by diatomites and MS and GD minima, were related to precession minima and obliquity maxima, indicating a link to the intensification of the North African monsoon in response to boreal summer insolation maxima. This is further supported by the simultaneous formation of diatomites with Mediterranean sapropels. The obliquity dominance might be explained by a combination of the cross-equatorial insolation gradient and the seasonal cycle of equatorial insolation, and/or a link to higher latitudes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".