SPATIAL AND TEMPORAL SIGNIFICANCE OF PROCESS ICHNOLOGY DATA FROM SILTY-MUDSTONE BEDS OF INCLINED HETEROLITHIC STRATIFICATION, LOWER CRETACEOUS MCMURRAY FORMATION, NE ALBERTA, CANADA
Bibliographic record
Abstract
Abstract In this paper we examine quantitative ichnological data of silty-mudstone beds from inclined heterolithic stratification (IHS) in order to understand the spatial and temporal controls affecting bioturbation in IHS. Data collected for this study include bed-scale averaged bioturbation intensity, size-diversity index, and ichnogenera abundances. These data were used to assign each bed into one of 10 clusters using K-Means clustering. The clusters were ranked according to interpreted intensity of cumulative depositional ecologic stress. Time-series, where each silty-mudstone bed represents a time-step with a corresponding ecologic stress value, were constructed from the interpreted ecologic stress cluster analysis results. To identify and interpret spatial and temporal variation in the ichnological time-series, two time-series analysis methods were employed: dynamic time-warping and continuous wavelet transforms. Dynamic time-warping is used as a descriptor of the spatial similarity between ecologic stresses, and continuous wavelet transforms are used to interpret cyclical patterns in the ichnological time-series. Spatially, the variability and cyclicity observed in the ecologic stress time-series can be linked to estuary scale stresses and more localized stresses (i.e., bar-form scale depositional stress). This is reflected by the relatively similar periodicities observed in the ecologic stress time-series. Temporally, cyclical ecologic stress patterns occur somewhat predictably in periods of approximately four, or multiples of four, which are consistent with El Nino cyclicity.
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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) | 0.001 | 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".