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Record W3191248006 · doi:10.1186/s42501-021-00099-9

Manganese carbonate stromatolites of the Ediacaran Doushantuo Formation in Chengkou, northern Yangtze Craton, China

2021· article· en· W3191248006 on OpenAlexaff
Yi Zhang, Jian Li, Long Chen, Wei Yi, Qiang Shi, Dong-Ge Wang, Qing-Ming Wu, Liao-Yuan Song, Meng Tian, Hongwei Kuang, Yongqing Liu, Kaarel Mänd, Huaqing Bai, Ziliang Liu, Yuchong Wang, Dawei Qiao, Wenjun Zhu

Bibliographic record

VenueJournal of Palaeogeography · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of Alberta
FundersBeijing Science and Technology Planning ProjectChina Geological SurveyMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsGeologyShoalManganeseCratonCarbonateSedimentary rockPaleontologyGeochemistryTectonicsGeomorphologyChemistry

Abstract

fetched live from OpenAlex

Abstract The origin process of manganese ores remains unsolved worldwide. Exploring the origins of stromatolites that contain manganese may be a key to deciphering the sedimentary environments and metallogenic processes of these deposits. However, only a few manganese stromatolites have been discovered and described until now. Microbialites are well developed in the manganese deposits, located near the top of the Ediacaran Doushantuo Formation in Chengkou area of Chongqing, northern Yangtze Craton, but has not been explicitly studied; and whether they are true stromatolites or Epiphyton microbialites remains controversial. Based on field and core observations and thin section microscopy, the characteristics of five types of manganese stromatolites and their growth modes are described in detail in this study. The results show that these stromatolites grew in a biostrome in shoal and lagoon environments and were syngenetic with oncolites and oolites on a carbonate ramp behind the shoal. Manganese stromatolites can be categorized into three forms: (1) stratiform; (2) columnar, which includes branched and columnar types; and (3) stratiform-columnar, which is a transitional type. Based on a criterion that the diameter is less than or greater than 1 mm, columnar stromatolites are further divided into micro-columnar (< 1 mm) and columnar (> 1 mm) columns, which display synchronous growth and are similar to Pseudogymnosolenaceae. Their shapes are mainly controlled by water depths and hydrodynamic strengths. The greater the water depth, the more columnar the columns tend to be. Excessively strong hydrodynamic conditions decrease the growth rate of stromatolites, and they even stopped growth due to wave damage. Furthermore, pillared laminar textures (not Epiphyton ), which consist of dendritic, micro-branched and micro-columnar stromatolites, are a common feature of the larger stratiform, stratiform-columnar and columnar stromatolites. The alternations of laminae with different internal textures record subtle fluctuations in water depths and hydrodynamic strengths, which indicate that stromatolite growth is controlled by tidal cycles at the lamina level. Therefore, it is possible that the vertical evolution of the stromatolites could reveal the changing characteristics of both local and regional sedimentary environments, i.e., stromatolite shape changes from columnar to stratiform can represent the onset of shallower environments with weak hydrodynamic conditions. In addition, as important reef builders in shallow carbonate ramps, microstromatolites accelerate the development from ramp to platform. Indicators of microbial control on stromatolite shapes and manganese sedimentation processes include the fabric of stromatolite laminae, organic rhodochrosite with a micritic texture that is usually clotted, spherical, tubular, fibrous or dendritic, which suggests that the laminae resulted from microbially induced in situ precipitation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.191
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

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