O<sup>18</sup>/O<sup>16</sup> ratios in snow and ice of the Hubbard and Kaskawulsh glaciers
Bibliographic record
Abstract
One hundred samples collected from the Hubbard and Kaskawulsh glaciers in the St. Elias Mountains during the summer of 1963 were analyzed for O18/O16 content. The δ18 values ranged from −18 to −29, with an average of about −23. Pits that were studied before extensive melting showed definite trends in δ18, with the more negative values corresponding to winter precipitation. Pits studied later in the season had the seasonal trend masked by the action of downward percolating meltwaters. The average of all pits and boreholes studied above the firn line gave no indication of an altitude variation of δ18 larger than the sampling error. A longitudinal profile below the firn line showed much scatter in the δ value, but the average trend was a decrease in δ18 in going down-glacier from the firn line to the terminus. A transverse profile below the firn line which sampled three main ice streams gave remarkably consistent values of δ near the margins, whereas the stream centers had decidedly more positive or negative δ values. These results are considered in terms of accepted modes of glacier flow. Precipitation studies exhibited much scatter and did not show the expected altitude variation of δ. Comparison of the over-all data with that of other workers shows a number of consistencies. This comparison also suggests that much of the precipitation in the area is derived from the Pacific Ocean rather than from inland sources.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".