Stable Isotopic Variability within Modern Travertines
Bibliographic record
Abstract
Six hot and two ambient water travertine systems were sampled to determine the relationships between the stable isotopic composition of the travertines and the waters from which they were deposited. This was conducted in order to evaluate the use of geochemical analyses of ancient travertines for the interpretation of the composition of the waters from which they precipitated, climatic conditions at time of formation, etc. The waters displayed down-flow trends of progressively higher (^ 8'3C values, in all 8 systems, and (H) 618O values, in all 6 hot water systems. Whereas the stable isotopic values of the mineral precipitates sometimes showed similar trends, the magnitude of the downflow changes commonly was quite different than that exhibited by the water data. Additionally, different types of precipitates, which formed within centimeters of each other, commonly had different stable isotopic compositions, e.g., crusts which formed at the air/water interface always had higher 813C and 8'8O values than constituents which formed within the immediately subjacent water column. The lack of a simple relationship between stable isotopic composition of the water and the precipitate is due to the fact that the stable isotopic composition of the precipitates are controlled by a number of variables, including the water's composition, temperature, level of saturation, etc. And these variables can change dramatically within very short distances and at the same spot within very short time intervals. Thus, as demonstrated by the stable isotope data, attempting to interpret the composition of the water from the composition of the deposit is a highly risky venture.
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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 | 0.001 | 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".