Maturation Impact on Polyaromatic Hydrocarbons and Organosulfur Compounds in the Carboniferous Keluke Formation from Qaidam Basin, NW China
Bibliographic record
Abstract
A maturity sequence from the Keluke Formation of the Upper Carboniferous marine–continental transitional depositional environment in the Qaidam basin, NW China has been geochemically characterized by bulk and molecular compositions, especially the behavior of polyaromatic hydrocarbons and organosulfur compounds. Some commonly used maturity parameters such as the methylnaphthalene ratio (MNR), the dimethylnaphthalene ratio (DNR), the methylphenanthrene ratio (MPR), methylphenanthrene index-3 (MPI-3), dimethylphenanthrene index-2 (DMPI-2), the methyldibenzothiophene ratio (MDR) and dimethyldibenzothiophene (DMDBT) ratios (4,6-/1,6- + 1,8- + l,4-DMDBT and 2,4-/1,6- + 1,8- + l,4-DMDBT), Rock-Eval T max, and measured vitrinite reflectance (% R o ) increase gradually with burial depth, whereas others such as the trimethylnaphthalene ratio (TMNr), the tetramethylnaphthalene ratio (TeMNr), MPI-1, and DMPI-1 show no correlation with these maturity indicators. The calculated equivalent R o values from MPR and MDR based on empirical correlation reported in the literature overestimate the maturity level. The degree of alkylation plays a dominant role in molecular compositional variation and maturity parameter validity, which is in turn controlled by the nature of organic input, depositional environment, and lithology rather than solely controlled by maturation. Dealkylation of alkylnaphthalenes at R o ∼ 1.0% removes most thermally unstable isomers from C3- and C4 homologues, which makes parameters based on them lose sensitivity. The proportion of phenanthrene varies greatly in the marine–continental transitional depositional system and the involvement of phenanthrene in the formulation makes MPI-1 and DMPI-1 fail to reflect the maturity level. Overestimation of the maturity level based on the degree of isomerization is caused by a high catalytic effect in the marine–continental transitional depositional system, which facilitates isomerization and dealkylation processes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".