Bibliographic record
Abstract
This success stems mainly from the intimate connection of ichnology with sedimentology and the importance of both fields for paleoenvironmental and basin analysis, which becomes more and more important in petroleum exploration. This useful connection, however, also had its price. In the hand of biogeologists, trace fossils easily lose their significance as unique biological documents. Dolf Seilacher Trace Fossil Analysis (2007) One of the triumphs of the palaeobiological approach to palaeontology is the insight functional morphology has given us about the life activities of long dead organisms. Richard Bambach, Andrew Bush, and Douglas Erwin “Autecology and the filling of ecospace: key metazoan radiations” (2007) Although the significance of trace fossils in paleoenvironmental reconstructions is responsible for the rapid development of ichnology, we should not forget that ichnofossils are produced by living organisms and, as such, the biological nature of trace fossils is at the core of any study on animal–substrate interactions. In this chapter, we analyze the paleobiological facet of trace fossils. In order to do so, we revise concepts from benthic ecology and paleoecology. First, we explore the concept of modes of life, addressing feeding strategy, position in relation to the substrate–water interface, and level of motility. Second, we elaborate on the different modes that organisms have to interact with and, in particular, penetrate into the substrate. Third, we look at basic locomotion and burrowing mechanisms from a historical perspective, revisiting the pioneering work of Schäfer and the synthesis by Trueman. We exemplify all these mechanisms with examples form the trace-fossil record. Finally, we close this chapter by introducing the new paradigm of movement ecology and its potential implications in ichnological studies.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".