Rates and processes controlling periglacial alluvial fan formation: Implications for martian fans
Bibliographic record
Abstract
Abstract Alluvial fans are found across a range of climates and are built from a combination of fluvial and debris flow processes. Correct identification of process is critical to reconstructing the climate and water histories of alluvial fans on Earth and Mars. Theory and data from subaerial Earth fans are often used to estimate paleoflow discharges and sediment fluxes for martian fans; however, most terrestrial work has been conducted on fans that are in hot, dry climates with runoff sourced from rainfall. This differs from the prevailing interpretation that martian fans were sourced from snowmelt under warming periglacial conditions. To characterize processes and rates of periglacial fan formation, we conducted a field-based study of the Black Mountain alluvial fan in the Aklavik Range, Canada. We observed active fluvial bedload transport as well as several small debris flows that had initiated from ice-filled gullies. Following a runoff event of ~0.005 mm/hr to ~0.2 mm/hr across the fan, we estimated sediment fluxes of ~0.04 m3/hr. Under bankfull conditions, we estimated runoff rates between ~0.01 mm/hr to ~14 mm/hr and corresponding sediment fluxes of ~0.3 m3/hr to ~550 m3/hr. This suggests that moderate flow events, well below the maximum runoff production rates suggested for Mars, are capable of entraining and transporting appreciable amounts of sediment by fluvial processes. However, sedimentological and geomorphological observations suggest that ~67% of the fan was deposited fluvially; the remainder was deposited by mass flows. Our results emphasize the need to take care in interpreting martian sedimentary processes and climate from fan surface morphology alone.
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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 | 0.000 | 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".