MARINE ORGANIC CARBON AND RADIOCARBON—PRESENT AND FUTURE CHALLENGES
Bibliographic record
Abstract
ABSTRACT We discuss present and developing techniques for studying radiocarbon in marine organic carbon (C). Bulk DOC (dissolved organic C) Δ 14 C measurements reveal information about the cycling time and sources of DOC in the ocean, yet they are time consuming and need to be streamlined. To further elucidate the cycling of DOC, various fractions have been separated from bulk DOC, through solid phase extraction of DOC, and ultrafiltration of high and low molecular weight DOC. Research using 14 C of DOC and particulate organic C separated into organic fractions revealed that the acid insoluble fraction is similar in 14 C signature to that of the lipid fraction. Plans for utilizing this methodology are described. Studies using compound specific radiocarbon analyses to study the origin of biomarkers in the marine environment are reviewed and plans for the future are outlined. Development of ramped pyrolysis oxidation methods are discussed and scientific questions addressed. A modified elemental analysis (EA) combustion reactor is described that allows high particulate organic C sample throughput by direct coupling with the MIniCArbonDAtingSystem.
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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 | 0.017 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".