Corrigendum to “Early precipitated micropyrite in microbialites: A capsule of microbial sulfur cycling” by Marin-Carbonne et al., 2022
Bibliographic record
Abstract
Correction to the Quasi Simultaneous Arrival effectAfter reviewing our work based on the suggestion of a careful reader, we have identified a miscalculation in the correction of the Quasi-Simultaneous Arrival (QSA) effect.This error affected the results presented in the article and was propagated to both the standard and sample data.The error has caused a slight change in the instrumental mass fractionation determination, resulting in a 2 ‰ shift in the corrected data.However, this correction remains negligible as corrected values remain within the error bars of each data.The average Δ pyr values for Lake Atexcac and Cayo Coco Lagoon are 61.4 ± 18.3 ‰ and 59.1 ± 29.6 ‰ respectively, which is consistent with the equilibrium sulfate-sulfide fractionation observed in natural settings with low microbial sulfate reduction respiration rates.However, the data distribution has slightly changed, as shown in the corrected Figure 4. Corrected Figure 4 (a) NanoSIMS 32 S image of submicrometric pyrites.(b) δ 34 S probability density function, taking account of the range of uncertainties from 1 ‰ to 8 ‰ of micropyrites from Cayo Coco (blue line) and Atexcac (green line).(c) Δ pyr distribution calculated for both environments, the average values are represented by the triangles.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.054 | 0.037 |
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".