Decoupling seasonal fluctuations in fluvial discharge from the tidal signature in ancient deltaic deposits: an example from the Neuquén Basin, Argentina
Bibliographic record
Abstract
Fluvial discharge fluctuations are a fundamental characteristic of almost all modern rivers and can produce distinctive deposits that are rarely described from ancient fluvial or mixed-energy successions. Large-scale outcrops from the Middle Jurassic Lajas Formation (Argentina) expose a well-constrained stratigraphic succession of marginal-marine deposits with a strong fluvial influence and well-known tidal indicators. The studied deposits show decimetre-scale interbedding of coarser- and finer-grained facies with mixed fluvial and tidal affinities. The alternation of these two types of beds forms non-cyclic successions that are interpreted to be the result of seasonal variation in river discharge, rather than regular and predictable changes in current velocity caused by tides. Seasonal bedding is present in bar deposits that form within or at the mouth of minor and major channels. Seasonal bedding is not preserved in channel thalweg deposits, where river flood processes were too powerful, or in floodplain, muddy interdistributary-bay, prodelta and transgressive deposits, where the river signal was weak and sporadic. The identification of sedimentary facies characteristic of seasonal river discharge variations is important for accurate interpretation of ancient deltaic process regime.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".