Aminopentol, a possible novel biomarker tracer for methane hydrate stability in sedimentary records
Bibliographic record
Abstract
Bacteriohopanepolyols (BHPs) are lipid membrane constituents of bacteria and occur with a wide range of structural and functional variability. Amino-BHPs are produced by methane-oxidising bacteria and the 35aminobacteriohopane-30,31,32,33,34-pentol (aminopentol) is a highly specific biomarker for aerobic methane oxidation. Aminopentol abundance varies significantly throughout the studied section with a suspected precessiondriven cyclical variability superimposed on longer-term short eccentricity cycles. Compound-specific stable carbon isotope analyses confirm that the amino-BHPs are of methanotrophic origin. A period of sustained greater concentrations and inferred emissions occurs from ca. 500 and 600 ka during which soil organic matter input, as recorded by soil BHP concentrations and the BIT index, is consistently low. Unsaturated 6 -bacteriohopanetetrol cyclitol ether, which is interpreted as a biomarker for nitrogen-fixing marine Tricodesmium cyanobacteria, was also found in this interval and is absent from the remainder of the section. This interval could therefore reflect a period of low terrigenous organic matter and associated nutrient input during which nitrogen-fixing bacteria may have flourished in the resultant nutrient-, in particular nitrate, poor water. Ongoing sea surface temperature reconstruction, using the TEX86 proxy, seeks to investigate potential perturbations in local climate with relation to these previously unrecognized methane emission events. The aerobic oxidation of methane is thought to be intrinsically linked with methane gas hydrate dissolution. Thus, the variability in amino-BHP abundance could provide an indicator for past methane emission events, directly linking key aspects of structural geology with gas hydrate stability, deep ocean processes, and methane cycling.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".