Sequence Stratigraphy: Methodology and Nomenclature
Bibliographic record
Abstract
The recurrence of the same types of sequence stratigraphic surface through geologic time defines cycles of change in accommodation or sediment supply, which correspond to sequences in the rock record. These cycles may be symmetrical or asymmetrical, and may or may not include all types of systems tracts that may be expected within a fully developed sequence. Depending on the scale of observation, sequences and their bounding surfaces may be ascribed to different hierarchical orders.Stratal stacking patterns combine to define trends in geometric character that include upstepping, forestepping, backstepping and downstepping, expressing three types of shoreline shift: forced regression (forestepping and downstepping at the shoreline), normal regression (forestepping and upstepping at the shoreline) and transgression (backstepping at the shoreline). Stacking patterns that are independent of shoreline trajectories may also be defined on the basis of changes in depositional style that can be correlated regionally. All stratal stacking patterns reflect the interplay of the same two fundamental variables, namely accommodation (the space available for potential sediment accumulation) and sediment supply. Deposits defined by specific stratal stacking patterns form the basic constituents of any sequence stratigraphic unit, from sequence to systems tract and parasequence. Changes in stratal stacking patterns define the position and timing of key sequence stratigraphic surfaces.Precisely which surfaces are selected as sequence boundaries varies as a function of which surfaces are best expressed within the context of the depositional setting and the preservation of facies relationships and stratal stacking patterns in that succession. The high degree of variability in the expression of sequence stratigraphic units and bounding surfaces in the rock record means ideally that the methodology used to analyze their depositional setting should be flexible from one sequence stratigraphic approach to another. Construction of this framework ensures the success of the method in terms of its objectives to provide a process-based understanding of the stratigraphic architecture. The purpose of this paper is to emphasize a standard but flexible methodology that remains objective.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.014 |
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".