Optically stimulated luminescence dating of late Holocene raised strandplain sequences adjacent to Lakes Michigan and Superior, Upper Peninsula, Michigan, USA
Bibliographic record
Abstract
This study evaluates the accuracy of optically stimulated luminescence to date well-preserved strandline sequences at Manistique/Thompson bay (Lake Michigan), and Tahquamenon and Grand Traverse Bays (Lake Superior) that span the past ∼4500 yr. The single aliquot regeneration (SAR) method is applied to produce absolute ages for littoral and eolian sediments. SAR ages are compared against AMS and conventional 14C ages on swale organics. Modern littoral and eolian sediments yield SAR ages <100 yr indicating near, if not complete, solar resetting of luminescence prior to deposition. Beach ridges that yield SAR ages <2000 yr show general agreement with corresponding 14C ages on swale organics. Significant variability in 14C ages >2000 cal yr B.P. complicates comparison to SAR ages at all sites. However, a SAR age of 4280 ± 390 yr (UIC913) on ridge77 at Tahquamenon Bay is consistent with regional regression from the high lake level of the Nipissing II phase ca. 4500 cal yr B.P. SAR ages indicate a decrease in ridge formation rate after ∼1500 yr ago, likely reflecting separation of Lake Superior from lakes Huron and Michigan. This study shows that SAR is a credible alternative to 14C methods for dating littoral and eolian landforms in Great Lakes and other coastal strandplains where 14C methods prove problematic.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".