A brief overview of modern directions in marine DOC studies Part I.—Methodological aspects
Bibliographic record
Abstract
The necessity for determining the role of dissolved organic carbon (DOC) in the global carbon cycle stimulated the development of different methods of DOC analysis in aquatic environments. Progress in this direction has been made by oceanographers who developed and introduced a high-temperature catalytic oxidation (HTC) method for low organic carbon concentrations. Today this method is the reference method for marine DOC study. The combination of available reference materials and the participation in intercalibration exercises has resulted in both an increased accuracy and higher precision for this method. The HTC method completely oxidizes the more resistant DOC; makes information rapidly available following the completion of the field analysis; provides a high precision (down to 0.5 microM C); covers the range of seawater DOC concentrations (35-80 microM C and higher); with certain modifications it has proved to be both seaworthy and amenable to automated analysis; and the reliable and relatively easy to operate HTC analyzer is commercially available and easily combined with a total nitrogen analyzer for simultaneous measurements of both parameters in the same sample. In this review we summarize some aspects of sample collection, handling and the analytical chemistry of the DOC analysis by the HTC technique in marine study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".