Energy Transfer Between the Geosphere and Biosphere
Bibliographic record
Abstract
abstract: One goal of geobiochemistry is to follow geochemical energy supplies from the external environment to the inside of microbial cells. This can be accomplished by combining thermodynamic calculations of energy supplies from geochemical processes and energy demands for biochemical processes. Progress towards this goal is summarized here. A critique of all thermodynamic data for biochemical compounds involved in the citric acid cycle (CAC) and the formulation of metabolite properties allows predictions of the energy involved in each step of the cycle as well as the full forward and reverse cycles over wide ranges of temperature and pressure. These results allow evaluation of energy demands at the center of many microbial metabolic systems. Field work, sampling, and lab analyses from two low-temperature systems, a serpentinizing system, and a subglacial setting, provide the data used in these thermodynamic analyses of energy supplies. An extensive literature summary of microbial and molecular data from serpentinizing systems found is used to guide the evaluation and ranking of energy supplies used by chemolithoautotrophic microbes. These results constrain models of the distribution of microbial metabolisms throughout the low-temperature serpentinization systems in the Samail ophiolite in Oman (including locales of primary and subsequent alteration processes). Data collected from Robertson Glacier in Alberta, Canada, together with literature data from Lake Vida in Antarctica and bottom seawater, allowed thermodynamic analyses of low-temperature energy supplies in a glacial system. Results for 1460 inorganic redox reactions are used to fully inventory the geochemical energy sources that support the globally extensive cold biosphere.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".