Seasonal temperatures from <i>δ</i><sup>18</sup>O in recent Spanish tufa stromatolites: Equilibrium redux!
Bibliographic record
Abstract
Abstract This study focuses on recent debate over the value of stable isotope‐based environmental proxies recorded in riverine tufa stromatolites. A twelve‐year record (1999 to 2012) of river‐bed tufa stromatolites in the River Piedra (north‐east Spain) was recovered in this study, along with a partly overlapping fifteen‐year record (1994 to 2009) of accumulations in a drainage pipe: both deposits formed in water with near identical physico/chemical parameters. Measured water temperature data and near‐constant δ18Owater composition allowed selection of an ‘equilibrium’ palaeotemperature equation that best replicated actual temperatures. This study, as in some previous studies, found that just two published formulas for water temperature calculation from equilibrium calcite δ18O compositions were appropriate for the River Piedra, where tufa deposition rates are high, with means between 5·6 mm and 10·8 mm in six months. The δ18Ocalcite in both the river and the pipe deposits essentially records the full actual seasonal water temperature range. Only the coldest times (water temperature <10°C), when calcite precipitation mass decreased to minimum, are likely to be unrepresented, an effect most noticeable in the pipe where depositional masses are smaller and below sample resolution. While kinetic effects on δ18Ocalcite‐based calculated water temperature cannot be ruled out, the good fit between measured water temperature and δ18Ocalcite‐calculated water temperature indicates that temperature is the principal control. Textural and deposition rate variability between the river and pipe settings are caused by differences in flow velocity and illumination. In the river, calcification of growing cyanobacterial mat occurred throughout the year, producing composite dense and porous laminae, whereas in the pipe, discontinuous cyanobacterial growth in winter promoted more abiogenic calcification. High‐resolution δ18Ocalcite data from synchronous pipe and river laminae show that reversals in water temperature occur within laminae, not at lamina boundaries, a pattern consistent with progressive increase in calcite precipitation rate as cyanobacterial growth re‐established in spring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".