Ichnodiversity and ichnodisparity: significance and caveats
Bibliographic record
Abstract
Ichnodiversity has been used as a proxy for environmental stress and stability in facies interpretations and to reconstruct evolutionary radiations and colonization histories in evolutionary palaeoecology. The three components of global diversity are exported from ecology and adapted for ichnology. Alpha ichnodiversity is used for palaeoenvironmental characterization, being assessed for individual facies. Beta ichnodiversity is commonly overlooked, although it may provide information about degree of similarity between ichnofaunas formed along environmental gradients. Gamma ichnodiversity may provide clues to detect ichnofossil provincialism. The concept of disparity may also prove to be significant in ichnological studies. Whereas ichnodiversity refers to ichnotaxonomic richness, ichnodisparity provides a measure of the variability of morphological plans in biogenic structures. Changes in global ichnodiversity do not necessarily parallel changes in ichnodisparity. For example, while the Cambrian explosion involved a dramatic increase in both, the Ordovician radiation essentially reflects an increase only in the former. Ichnodiversity and ichnodisparity should be used with caution because they are both affected by taphonomic processes. High diversity of superficial to shallow-tier trace fossils may result from enhanced preservation due a poorly developed mixed layer, rather than a true reflection of ecosystem performance, as shown by underexploited infaunal ecospace after biotic crises (e.g. end-Permian mass extinction).
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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 | 0.047 | 0.217 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.016 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".