Quantifying Sources and Transport Pathways of Surface Sediments in the Gulf of San Jorge, Central Patagonia (Argentina)
Bibliographic record
Abstract
The Gulf of San Jorge (GSJ) is a semicircular basin, approximately 160 km long and 250 km wide, located in the central part of Patagonia between 45°S and 47°S, lacking any present-day major perennial tributaries. The grain size and bulk and clay mineralogical compositions as well as major and minor elements of 75 surface sediment samples from the GSJ and the adjacent continental shelf were investigated to define the spatial distribution, transport pathways, and potential sources of terrigenous material. To better constrain the origins of GSJ sediments, analyses were also performed on 14 terrestrial, riverine, and marine samples from potential source areas around the gulf and Patagonia. The mineral assemblage of surface sediments in the gulf, dominated by plagioclase, quartz, and clays, is a function of the primary continental volcanic geology of Patagonia. The significant concentration of volcaniclastic particles indicated by mineralogical signatures and scanning electron microscope images of sediments suggests a substantial contribution from rhyolitic volcanism to the modern sedimentation in the gulf. High amounts of smectite are carried into the GSJ by dust transport, whereas inputs of chlorite and illite seem to be associated with continental shelf current transport from southern Patagonia. Finally, our results suggest that 50% of the surface sediment in the GSJ is derived from external/oceanic inputs, 40% from inner gulf shores (i.e., erosion and runoff), and 10% from dust (i.e., aeolian transport).
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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 | 0.001 | 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) | 0.000 | 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 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".