Review of the manuscript “Dissolved iron in the North Atlantic Ocean and Labrador Sea long the GEOVIDE section (GEOTRACES section GA01)” submitted by M. Tonnard et al.
Bibliographic record
Abstract
The paper submitted discusses the distribution and sources of DFe along the GA01 transact in the North Atlantic.The included DFe data looks great and is of big interest for the entire GEOTRACES community.Thus the manuscript is suitable for Biogeosciences.However, apart from the introduction and MM section, large parts of the result, discussion and conclusion section need substantial overhaul before the article can be published.I recommend major revision.One of the biggest difficulties for me was to follow their argumentation in paragraphs.The authors did a great job to include large amounts of ideas and literature findings C1 BGD Interactive commentPrinter-friendly version Discussion paper in each paragraph to explain their DFe distribution.However, in most cases the final outcome drowns by too much detail and unnecessary sentences that do not contribute to the finding.Another problem I had, some discussions were performed superficial.When the authors discuss the aerosol distribution and DFe, for instance, they focus on elemental ratios and argue then, that not enough soluble Fe from aerosol particles was introduced.You may be able to get some insight about DFe and dust, by comparing fluxes and residence times, but not with ratios.You can use ratios to pinpoint sources, but quantitative assumptions are highly uncertain.My recommendations are listed below!However, I see the great potential of the paper, which will help to understand the DFe cycle in the high latitudinal ocean, between the artic and subtropics.In addition, reduces blind spots in the GEOTRACES map (IDP).Anyway, I am happy to review a revised version of the manuscript!With best regards, Christian
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.092 | 0.065 |
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".