Distinction between the Youngest Toba Tuff and Oldest Toba Tuff from northern Sumatra based on the area density of spontaneous fission tracks in their glass shards
Bibliographic record
Abstract
Abstract Determination of the area density of spontaneous fission tracks (ρs) in glass shards of Toba tephra is a reliable way to distinguish between the Youngest Toba Tuff (YTT) and the Oldest Toba Tuff (OTT). The ρsvalues for YTT, uncorrected for partial track fading, range from 70 to 181 tracks/cm2with a weighted mean of 108 ± 5 tracks/cm2, based on 15 samples. Corrected ρsvalues for YTT are in the range of 77–140 tracks/cm2with a weighted mean of 113 ± 8 tracks/cm2, within the range of uncorrected ρsvalues. No significant difference in ρsexists between YTT samples collected from marine and continental depositional settings. The uncorrected ρsfor OTT is 1567 ± 114 tracks/cm2so that confusion with YTT is unlikely. The ρsvalues of the Toba tephra at Bori, Morgaon, and Gandhigram in northwestern India indicate a YTT identity, in agreement with geochemical data on their glass shards, the presence of multiple glass populations, and a glass fission-track age determination. Therefore, the view of others that OTT is present at these sites – and thereby indicates an early Pleistocene age for the associated Acheulean artifacts – is incorrect.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".