The Chemical, Physical, and Microbial Origins of Pleistocene Cherts at Lake Magadi, Kenya Rift Valley
Bibliographic record
Abstract
The cherts in the Magadi basin have long been considered to be a product of the diagenesis of the rare, inorganically-precipitated, soft sodium-silicate mineral, magadiite (forming “Magadi-type chert”). While this process is known to have occurred in the basin, not all chert necessarily formed from diagenetic conversion of this mineral, as there are several features to suggest other mechanisms of silica deposition alternative to that of magadiite. Lake Magadi, in the southern Kenya rift, shows a highly geochemically evolved closed lake system rich in dissolved Na-CO3-Cl, that has produced many unique sedimentary deposits throughout its geological history. Sediments deposited in the Magadi Basin from the mid- to late Pleistocene host many distinct varieties of lacustrine chert, which formed as a result of tectonic, climatic, microbial, and geochemical processes. The form, distribution, morphology, and abundance of cherts in the Magadi basin has drawn many researchers to consider their origin and diagenesis. The aim of this study is to reassess ideas about the origins of the siliceous sediments and rocks exposed in the Magadi basin. Of the four recognized sedimentary units in the Magadi Basin, chert occurs in three of them. The oldest cherts, found in the Oloronga Beds (800 to 300 ka), are diatomaceous in composition, and were excluded from this study. A staggering amount of the chert in the Magadi Basin (95%) belongs to the Green Beds (98 to 40 ka), a recently defined sedimentary unit. Features in many of the Green Beds cherts imply a potential microbial influence during precipitation of the precursor material, and also a possible relationship with hot springs. The High Magadi Beds (24 to 9 ka) are host to definitive Magadi-type cherts, with distinct macro- and microscopic features allowing for their identification (reticulate patterning, and “grid-like” precipitation of chalcedony, respectively). The Green Beds cherts have not been studied in detail since the introduction of this previously undefined sedimentary unit (Behr & Röhricht, 2000; Behr 2002). Microscopic evidence of preserved microbial remains in Magadi chert is indistinct, but macroscopic evidence of microbial influence is extensive (e.g., petee and tepee structures in chert;couplets and triplets of thin, banded chert layers). Extensive bedded chert layers crop out in a few locations around the basin, displaying evidence of a shallow, evaporative environment (e.g., preserved salt crystal casts on chert surfaces). Geothermal influence at the time of silica precipitation is inferred by macroscopic, geochemical, and analogous observations (e.g., a possible hot spring vent mound composed of chert; geochemical signatures; modern Na-Al-Si gels precipitating near hot spring inflow in Nasikie Engida). Perennial lagoons, sustained by warm springs issuing along the faulted margins of the basin, are observable to this day. Spring activity is locally observable, as perennial peripheral lagoons, and can also be inferred as a past process. Geothermal activity occurs along long-lived fault lines, and the surface expression of these tectonic features is distinctly discernible across the modern landscape (horsts and graben tectonism that can be playfully referred to as a “piano key landscape”). Whereas “Magadi-type chert” was once used to describe all chert in the basin, and was also thought to form in a deep, stratified lake, many lines of evidence exist to suggest siliceous-gel-like precursors, and a shallow, evaporative, and geothermally-influenced environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".