Bioturbation Intensity: A Proxy for Evaluating Environmental Stresses in the Bluesky Formation, Northeastern Alberta
Bibliographic record
Abstract
The late Aptian to early Albian Bluesky Formation comprises complex marginal marine environments, for which the stratigraphic correlations are poorly understood (Hubbard et al. 1999). As such, several depositional models have been proposed (e.g. Brekke, 1995; Hubbard et al., 1999, 2002; MacKay and Dalrymple, 2005, 2011). These interpretations differ not only in their broad environmental affinities (e.g. delta, estuary, barrier island) but also in the dominant physical processes affecting the system (wave-dominated vs. tide-dominated). This study attempts to use bioturbation intensity (BI) and ichnofossil assemblages to establish the primary environmental stresses present during the deposition of the Bluesky Formation. Stresses affecting burrowing organisms include high sediment deposition rates, salinity fluctuations, reduction of bottom water/substrate oxygenation, elevated water turbidity, prolonged subaerial exposure, introduction of substrates that limit burrowing, and variations in energy conditions (MacEachern et al., 2010). These stresses affect ichnological characteristics such as ethology (behaviors) and trace fossil assemblages. With the incorporation of ichnological characteristics, lithology, physical structures and lithological details (i.e. pebble lags, shell fragments, coal, etc.), the establishment of reliable facies interpretations is possible.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".