Assessing Geochemical Bioenergetics and Microbial Metabolisms at Three Terrestrial Sites of Serpentinization: The Tablelands (NL, CAN), The Cedars (CA, USA), and Aqua de Ney (CA, USA)
Bibliographic record
Abstract
Abstract The subsurface process of serpentinization creates an extreme environment for microbial life. This environment includes reducing, ultra‐basic groundwater that is limited in electron acceptors. Despite these challenging conditions, there is a great deal of potential energy available to support microbial metabolisms both in the anaerobic subsurface and in aerobic surface environments where serpentinization associated groundwater discharges. In this study, the available energy was quantified through the calculation of chemical affinities, Ar, for three sites of active serpentinization in North America: the Tablelands (NL, CAN), The Cedars (CA, USA), and Aqua de Ney (CA, USA). The results showed that Ar values for each reaction were similar for all sites studied; however, the available energy varied a great deal from reaction to reaction. For example, the reaction of carbon monoxide oxidation provided the most energy to the system followed closely by hydrogen oxidation and methanotrophy. Potential microbial metabolisms were tested, simulating surface and subsurface conditions, in a laboratory‐based setting using microcosms with materials from each site. During these microcosm experiments, carbon monoxide oxidation was not observed, and there was little evidence of methane oxidation. Unexpectedly, microbial methanogenesis was observed in methane oxidation microcosms using material collected from The Cedars. The microbial production of methane occurred despite the addition of electron acceptors demonstrating the broad tolerance of methanogens at The Cedars for less reducing conditions.
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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 | 0.001 |
| 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".