Progress in ESR and U-Series Chronology of the Levantine Paleolithic
Bibliographic record
Abstract
Any study of the origins of humans must be set in a chronological context. Prehistorians now have available to them a reasonably large set of tools with which to assign ages to events of the past. Radiocarbon is essentially useless as a tool for the time range under discussion here: In samples older than about 40 ka, the atoms originally deposited with the sample have decayed to less than 1% of their initial value, while equal or greater amounts of contaminant atoms may be present. Newer dating methods now exist which are based on the measurement of doses of radioactivity trapped in natural or artificial materials. While these methods can span the time range, they can also extend much further back in time, and are applicable to a wide variety of archaeological deposits. While their normal precision of 10% is much less than that of dating, they do not require independent calibration. These methods encompass the following: thermoluminescence (TL) dating of burned flint artifacts (Valladas et al., this volume); opticaland infrared-stimulated luminescence (OSL, IRSL) dating of wind-blown sand and silt (e.g., desert loess) which has been zeroed by solar bleaching; and electron spin resonance (ESR) dating of tooth enamel of larger mammals. Some of the physical parameters used to determine the age are shared by all these methods (external dose rate, water content of sediment) while others are unique to each method and sample type (e.g., internal dose rate) and assure that these various methods provide dates that are largely independent of one another. For example, ESR ages at a site may largely depend on the internal uranium content of the tooth sample and its uptake history, whereas TL dates on flint at the same site may depend equally on internal and external dose rates. Over the past decade there has also been an order-of-magnitude increase in the precision of uranium-series (US) dating through the advent of thermal ionization mass spec-
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".