The Microstructural Record of Predation: A New Approach for Identifying Predatory Drill Holes
Bibliographic record
Abstract
Abstract Drill holes in prey skeletons are the most common source of data for quantifying predator-prey interactions in the fossil record. To be useful, however, such drill holes need to be identified correctly. Field emission scanning electron microscopy (FE-SEM) and environmental scanning electron microscopy (ESEM) were applied to describe and quantify microstructural characteristics of drill holes. Various specimens, including modern limpets and mussels drilled by muricid snails in laboratory experiments, subfossil limpets collected from a tidal flat (San Juan Island, Washington state, USA), and various Miocene bivalves collected from multiple European sites, were examined for microstructural features. The microstructures observed are interpreted here as Radulichnus-like micro-rasping marks, or predatory microtraces, made by the radula of drilling gastropod predators. The mean adjacent spacing of these microtraces is notably denser than the spacing of muricid radular teeth determined by measurements taken from the literature. Because the radular marks typically overlie or crosscut each other, the denser spacing of predatory microtraces likely reflects superimposition of scratches from repeated passes of the radula. One incomplete drill hole showed a clear, chemically aided drilling dissolution signature around its outer margin, while a number of other specimens showed similar, but ambiguous, traces of dissolution. The range of organisms examined illustrates the utility of scanning electron microscopy (SEM) imaging for identifying micro-rasping marks associated with predatory drill holes in both modern and fossil specimens. These distinct microtraces offer promise for augmenting our ability to identify drill holes in the fossil record and to distinguish them from holes produced by non-predatory means.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".