Experimental studies on New Zealand hot spring sinters: rates of growth and textural development
Bibliographic record
Abstract
To study the rate of growth of sinters in New Zealand hot springs, field experiments were conducted in seven geothermal areas. At Wairakei, fan-shaped subaqueous deposits of amorphous silica grow rapidly (350 kg a1 m2 of drain wall) and are composed of silicified filaments with subordinate bacillus and spirillium-shaped organisms. Characterization of bacteria revealed isolates sharing > 97% 16S rRNA gene sequence homologies affiliated with Thermus, Meiothermus,Bacillus, Tepidomonas, Thermomonas, Porphyrobacter, Thermonema, and, Hydrogenophilus spp., as well as previously uncultured bacteria. At Rotokawa, microstromatolites have a slow growth rate (0.004 mm day1) that is attributed to low pH, capillary rise, and evaporation. At Champagne Pool, sinter growth (0.023 mm day1) is dominated by wave action building alternating microbe-rich and microbe-poor layers. Silica sinter was not observed at Waikite, where slides developed a layer of calcite (0.026 mm day1). Sinter growth at Ngatamariki (0.016 mm day1) forms by capillary rise, evaporation, and diffusion and at Tokaanu, subaqueous growth is slow (0.002 mm day1) and contains silicified microbes. Textures at Orakei Korako indicate similar mechanisms to Ngatamariki, except that growth is more rapid (0.023 mm day1) due to a splash contribution. Silica and calcite saturation indices adequately explain the growth of the sinters and calcite, indicating that microbes are not inducing precipitation where it should not occur. The rate of precipitation is correlated with silica supersaturation, but pH effects can alter this relationship. The degree of preservation of microbial material is explained by the effect of Ostwald ripening on silica spherules. Subaqueous growth allows coarsening of spherules and poor preservation of smaller microbes while subaerial nucleation is rapid, Ostwald ripening is inactive, and better preservation can be expected.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".