Variations in Water Content in Opal-A and Opal-CT from Geyser Discharge Aprons
Bibliographic record
Abstract
Abstract Opal-A (SiO2·nH2O) and its diagenetic derivative, opal-CT, are found in environments that range from the deep ocean floor to terrestrial spring/geyser systems. Although the loss of water may be a critical factor in the transition from opal-A to opal-CT, analytical difficulties in determining the distributions and quantities of molecular water (H2Omol) and silanols (H2OSiOH) has hindered a full understanding of the processes involved with this diagenetic transition. Electron microprobe (EMP) and micro–Fourier transform infrared (FTIR) analyses of opal-A and opal-CT collected from geyser discharge aprons on Iceland and the North Island of New Zealand produce compatible and reliable derivations of the total weight % water in opal-A and opal-CT, provided that they contain < 1 wt % of other elements such as Al. EMP analyses produce excellent results where microscale variations in total water content are required but it cannot determine if that water is formed of molecular water (H2Omol) or silanols (H2OSiOH). In contrast, FTIR analyses yield total water, molecular water, and silanol contents of the opal. Microscale variations, however, are commonly masked because the scale of FTIR analysis is coarser than that for EMP analyses. Analyses of sinters from Iceland and New Zealand show that the opal-A contains 2.1–12.1 (average 7.3) wt % total water whereas the opal-CT contains 1.0–8.9 (average 5.5) wt % total water. Based on FTIR analyses, the opal-A contains 1.2–9.8 (average 6.8) wt % molecular water and 0.4–2.4 (average 1.0) wt % silanols compared to opal-CT, which contains 3.8–8.2 (average 6.7) wt % molecular water and 0.1–0.7 (average 0.2) wt % silanols. The dual usage of EMP and FTIR analyses provide important information on the distribution of different types of water in opal-A and opal-CT, irrespective of the environments where they formed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".