Comparing Rhizon samplers and centrifugation for pore‐water separation in studies of the marine carbonate system in sediments
Bibliographic record
Abstract
Abstract An accurate description of the carbonate system in pore waters is valuable in studies involving the degradation of sedimentary organic matter, recrystallization of calcium carbonate minerals, calculations of mineral saturation state, and cycling of ions affected by pH. Here, we analyze water chemistry of pore water extracted using centrifugation and Rhizon samplers from hemipelagic sediments in the Gulf of Aqaba, Red Sea, and a shallow salt marsh from Norfolk, England. In both study areas, the data are internally consistent for each pore‐water separation technique, but the measured isotopic composition of the dissolved inorganic carbon (δ13C[DIC]) differs between the two techniques. We performed laboratory experiments that show that both Rhizons and centrifugation are prone to degassing of CO2 enriched with 12C. We suggest that during sampling with Rhizons, air fills the voids left by extracted pore water; combined with the membrane's design to exclude air, some of the aqueous CO2 diffuses into these air bubbles instead of the sampler. Rhizons produce reliable calcium, strontium, manganese, and barium concentration data when soaked in deionized water and then flushed with the sample immediately prior to sampling. However, pore‐water extractions with Rhizons are less reliable for analyses of pH and δ13C[DIC]. Centrifugation produces reliable carbonate chemistry and major element data when tubes are fully filled without headspace and sealed tightly. Working in CO2 low/free atmosphere (e.g., N2 glovebox) enhances the chance of losing CO2 from the sample in both sampling techniques due to increased negative gradient of CO2 between the core and its surrounding.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".