A time series of incubation experiments to examine the production and loss of CH<sub>3</sub>I in surface seawater
Bibliographic record
Abstract
Abstract In order to investigate production pathways of methyl iodide and controls on emissions from the surface ocean, a set of repeated in vitro incubation experiments were performed over an annual cycle in the context of a time series of in situ measurements in Kiel Fjord (54.3°N, 10.1°E). The incubation experiments revealed a diurnal variation of methyl iodide in samples exposed to natural light, with maxima during day time and losses during night hours. The amplitude of the daily accumulation varied seasonally and was not affected by filtration (0.2 µm), consistent with a photochemical pathway for CH 3 I production. The methyl iodide loss rate at nighttime correlates with the concentration accumulated during daytime suggesting a first‐order loss mechanism (R 2 = 0.29, p << 0.01). Daily (24 h) net production (P net ) was similar in magnitude between in vitro and in situ mass balances. However, the estimated gross production (P gross ) of methyl iodide ranged from −0.07 to 2.24 pmol L −1 d −1 and was up to 5 times higher in summer than P net calculated from the in situ study. The large excess of P gross over P net in summer revealed by the incubation experiments is a consequence of large losses of CH 3 I by as‐yet uncharacterized processes (e.g., biological degradation or chemical pathways other than Cl − substitution).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".