Magnetic mineral transport and sorting in the swash‐zone: northern Lake Erie, Canada
Bibliographic record
Abstract
Abstract A combined field and laboratory study in northern Lake Erie has provided new insights into the origin and dynamics of heavy mineral placer deposits on beaches consisting primarily of non‐magnetic sediment. Work was conducted on the cross‐shore and longshore transport of heavy magnetic minerals using magnetic susceptibility and fluorescent paints to trace the movement, in the field, of samples of magnetic (magnetite) and non‐magnetic (quartz and calcite) grains, respectively. Laboratory experiments examined how the burial of small, dense magnetic minerals is affected by the grain size of the non‐magnetic host material, and how grain burial affects magnetic susceptibility measurements at the surface. The field experiments demonstrated that the magnetic mineral tracers were buried rapidly beneath coarser, non‐magnetic grains under low to moderate wave conditions, and subsequently were unable to move in the longshore or cross‐shore directions. The laboratory experiments showed that the magnetic susceptibility rapidly decreased with the rate and depth of burial of the magnetic minerals, and that magnetic grain burial was most effective beneath coarser rather than finer non‐magnetic sand and, for the latter sediments, under less rather than more energetic conditions. The results imply that magnetic mineral concentrations develop in this area through magnetic grain burial under fairly mild conditions, and subsequent settling, exposure and concentration in the upper swash zone during more energetic periods, when the non‐magnetic grains are eroded. It is probably during these erosional periods, when the magnetic minerals are exposed in fairly homogeneous deposits, that longshore and cross‐shore transport takes place.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".