Animal bioturbation preserved in Pleistocene magadiite at Lake Magadi, Kenya Rift Valley, and its implications for the depositional environment of bedded magadiite
Bibliographic record
Abstract
O)], was discovered about 50 years ago in sediments around Lake Magadi, a hypersaline alkaline lake fed by hot springs in the semi-arid southern Kenya Rift Valley. Today this harsh lacustrine environment excludes most organisms except microbial extremophiles, a few invertebrates (mostly insects), highly adapted fish (Alcolapia sp.), and birds including flamingos. Burrows discovered in outcrops of the High Magadi Beds (~25-9 ka) that predate the modern saline (trona) pan show that beetles and other invertebrates inhabit this extreme environment when conditions become more favourable. Burrows (cm-scale) preserved in magadiite in the High Magadi Beds are filled with mud, silt and sand from overlying sediments. Their stratigraphic context reveals upward-shallowing cycles from mud to interlaminated mud-magadiite to magadiite in dm-scale units. The burrows were formed when the lake floor became fresher and oxygenated, after a period when magadiite precipitated in shallow saline waters. The burrows, probably produced by beetles, show that trace fossils can provide evidence for short-term (possibly years to decades) changes in the contemporary environment that might not otherwise be recognised or preserved physically or chemically in the sediment record.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".