Current concepts in mudstone description and deposition: A synthesis for mudstone initiates
Bibliographic record
Abstract
Conventionally, geologists have regarded mudstones as deposits formed through suspension settling in environments located at the terminus of sediment transport pathways, with the sediment sourced from a mix of detrital inputs into the basin and in situ production within the basin. However, mudstones are sedimentologically enigmatic as they are characterized by intricate small-scale features. Analysing mudstones with the typical techniques used for coarse grained siliciclastics does a disservice to the intricacies of these deposits. Grains, pores, and depositional fabrics within these rocks are not visible in hand sample, and often not even at the petrographic scale. Study of these features, at appropriate scales, can generate valuable insights into the physical and chemical conditions of their deposition. Along with analytical techniques, the conventionally held interpretations of these rocks are out of date. New insights into the origins and composition of grain components reveal significant variability, indicating these deposits are much more complex than traditionally understood. As a result, historical nomenclature and interpretation paradigms have undergone significant revision. However, there is still more research needed to fully address the challenges of mudstone description, classification and interpretation. This paper presents digestible discussions of changes in mudstone paradigms, the most effective practices consistent with modern understandings of mudstones, and considers areas that merit further consideration. Ideas presented herein are aimed at all those interested in mudstones, but is primarily meant for those new to the challenge of conducting mudstone analyses. Herein we recognize several preferred practices that have gained consensus in the literature, these include: (1) clearly defining common historical terms such as ‘clay’, ‘silt’, ‘bed’, and ‘shale’ depending on modern chosen usage; (2) outlining the transportational (i.e., functional) grain size of the deposit, as many constituents may be transported as amalgamated clasts; (3) clearly defining if reported mudstone composition is based on transported or apparent grain size (i.e., individual grain measurements); (4) thin section preparation methods and their integration with other complementary analytical techniques. As well, we discuss: (1) the use of both petrographic trace fossil analysis and microfacies analysis; (2) complex depositional mechanisms, beyond suspension settling, that lead to the accumulation of fine-grained deposits; and, (3) the interaction of several variables involved in accumulating organic-rich deposits. Ultimately, when embarking on mudstone analysis, one must first decide what question they are trying to answer. This will dictate the approach used, and if the focus is on the intricacies of grain size, composition, or depositional fabric.
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 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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".