Isotopic data of pyrite (δ34S) and barite (δ34S, δ18O) in the Canol Formation (Selwyn Basin, Canada)
Bibliographic record
Abstract
The stable isotopic composition of pyrite (δ34Spyrite) and barite (δ34Sbarite, δ18Obarite) in marine sedimentary rocks provides a valuable archive for reconstructing the biogeochemical processes that link the sulfur, carbon, and iron cycles. Highly positive δ34Spyrite values that exceed coeval unmodified seawater sulfate (δ34Spyrite > δ34SSO4(SW)), have been recorded in both modern sediments and ancient sedimentary records and are interpreted to result from various biotic and abiotic processes under a range of environmental conditions. A host of processes, including basin restriction, euxinia, low seawater sulfate, dissimilatory microbial sulfate reduction, sulfide reoxidation, and sulfur disproportionation, have been suggested to account for the formation of highly positive δ34Spyrite values in marine environments. Significantly, determining which of these factors was responsible for the pyrite formation is impeded by a lack of constraints for coeval sulfate, with relatively few examples available where δ34Spyrite and proxies for δ34Ssulfate values (e.g., barite) have been paired at high resolution. In the Selwyn Basin, Canada, the Late Devonian sedimentary system is host to large, mudstone-hosted bedded barite units. These barite units have been interpreted in the past as distal expressions of SEDEX mineralization. However, recent studies on similar settings have highlighted how barite may have formed by diagenetic processes before being subsequently replaced during hydrothermal sulfide mineralization. Coincidentally, highly positive δ34Sbarite values have been recorded in such barite occurring coevally with pyrite in diagenetic redox front, where sulfate reduction is coupled to anaerobic oxidation of methane (SR-AOM) at the sulfate methane transition zone (SMTZ). The mechanisms of sulfur cycling and concurrent processes are, nevertheless, poorly constrained. Grema et al. (2021) integrate high-resolution scanning electron microscopy petrography of barite (+ associated barium phases) and pyrite, together with microscale isotopic microanalyses of δ34Spyrite, δ34Sbarite, and δ18Obarite of selected samples from the Late Devonian Canol Formation of the Selwyn Basin. Samples containing both barite and pyrite were targeted to develop paired isotopic constraints on the evolution of sulfur during diagenesis. We have focused on the precise mechanism by which highly positive δ34Spyrite values developed in the Canol Formation and discuss the implications for interpreting sulfur isotopes in similar settings. This data report comprises microscale secondary ion mass spectrometry (SIMS) analyses of the isotopic compositions of pyrite (δ34Spyrite; n= 200) and barite (δ34Sbarite; n= 485, δ18Obarite; n= 338) in nine stratigraphic sections of the Northwest Territories’ part of the Selwyn Basin. Microdrills of regions of interest (n= 54) were made on polished sections to obtain suitable subsamples, using a 4 mm diameter diamond core drill. Several representative subsamples were cast into 25 mm epoxy pucks, together with reference materials (RMs) of pyrite S0302A (δ34S V-CDT = 0.0 ± 0.2‰ (Liseroudi et al., 2021)) and barite S0327 (δ34SV-CDT = 11.0 ± 0.5 ‰; δ18OV-SMOW = 21.3 ± 0.2 ‰ (Magnall et al., 2016)). Microscale isotopic analyses were carried out using Cameca IMS1280 large-geometry secondary ion mass spectrometer (SIMS) operated in multi-collector mode at the NordSIMS laboratory, Stockholm, Sweden. External analytical reproducibility (1 σ) was typically ± 0.04‰ δ34S for pyrite, ± 0.15‰ δ34S, and ± 0.12‰ δ18O for barite. The sample identification, location, and depth are reported in the data files.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".