Ichnology of shallow-marine clastic environments
Bibliographic record
Abstract
As discussed in other chapters of this book, traces commonly receive a paleontologic or zoologic connotation. Because of this aspect, traces are often given a short shrift by sedimentologists. This situation is unfortunate, and indeed unfair, to the study of sediments because the contained lebensspuren are sedimentary structures (albeit biologically formed) and should receive attention equal to that devoted to structures developed by physical processes. In fact, these traces often supply evidence of sedimentological conditions that is superior to information gained only by the study of physical structures. If the foregoing is not sufficient reason for sedimentologists to be concerned with the study of ichnology, perhaps they can be prodded into it by virtue of the fact that the nefarious beasts creating the biogenic structures have a nasty habit of destroying their beloved physical structures, and they should at least attempt to identify the enemy! Jim Howard “The sedimentological significance of trace fossils” (1975) Historically, one of the major strengths of ichnology is its utility in facies analysis and paleoenvironmental reconstructions. Undoubtedly, marine ichnology has been the main focus of most trace-fossil research in this respect. However, our knowledge of marine ichnofaunas is still uneven. The vast majority of ichnological studies applied to facies analysis and paleoenvironmental reconstruction deals with ichnofaunas from siliciclastic successions, rather than carbonates, mixed carbonates-clastics, or volcaniclastics. In siliciclastic settings, both shallow- and deep-marine ichnofaunas have received similar attention. However, ichnological studies in shallow-marine environments have attained better integration with sedimentological data than those in deep-marine settings. In turn, the ichnology of wave-dominated shallow-marine environments has been explored in more detail than their tide-dominated counterparts. In connection with this, the ichnological content of sandy shores is much better known than that of muddy coasts. In fact, some specific types of muddy shorelines, such as chenier plains (e.g. Augustinus, 1989), remain essentially unrecognized in the geological record. Also, end members, with respect to wave and tidal dominance, are better understood than mixed systems (e.g. Anthony and Orford, 2002). In this chapter, we will review the ichnology of different shallow-marine clastic environments, covering wave-dominated, tide-dominated, mixed systems, and muddy shorelines.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".