The Effects of Spatial Patchiness on the Stratigraphic Signal of Biotic Composition (Type Cincinnatian Series; Upper Ordovician)
Bibliographic record
Abstract
Abstract Patchiness affects fine-scale patterns of biological variation because compositional differences among localities depend on the composition of the patch sampled for paleoecological analysis. This can inflate compositional differences among localities that otherwise may have similar faunal constituents, which can obscure the true signal of biotic composition. In the type Cincinnatian Series, comparisons of fine-scale faunal-assemblage patterns acquired through gradient analysis have been difficult to accomplish because of significant deviations in biotic composition. Here, the role of patchiness in creating these deviations is tested by quantifying the amount of lateral variation in composition at a single outcrop of the Kope Formation. Because the lateral expression of individual beds in the Cincinnatian is variable, patchiness is more effectively assessed for bedsets rather than individual beds. Using gradient analysis to evaluate lateral variation at one locality reveals that patchiness is the cause of fine-scale stratigraphic deviations, which are typically produced by the addition or subtraction of just a few taxa. Furthermore, this lateral variability is less for limestone bedsets than for many mudstone bedsets. This supports the idea that limestone beds in the Cincinnatian contain assemblages that are more time-averaged than many, though not all, mudstone beds. Because fine-scale faunal patterns are dependent on the composition of the sampled patch, replicate sampling is necessary to account for patchiness. Despite the effects of patchiness and time-averaging at scales of one or a few beds, biotic composition patterns acquired through gradient analysis are robust among localities at scales greater than a few beds.
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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".