Clumped-isotope evidence for the formation of nonplanar dolomite textures at near-surface temperatures—Reply
Bibliographic record
Abstract
We appreciate the attention that Gregg ( 2024) brings to our recent article in the Journal of Sedimentary Research.In this article, Ryan et al. (2023) use petrographic and D 47 data from nine dolomite samples in the Paleocene-Eocene Umm er Radhuma Formation in Qatar to show that nonplanar dolomite textures can form below the theoretical dolomite critical roughening temperature (CRT) proposed by Gregg and Sibley (1984).From our reading, the key criticisms of Gregg (2024) can be summarized as follows: i) the dolomites presented in Ryan et al. (2023) do not exhibit nonplanar textures, ii) the D 47 -derived temperatures presented in Ryan et al. (2023) do not accurately reflect the conditions during dolomite crystallization, and iii) Ryan et al. ( 2023) unfairly criticize the kinetic theory of crystal growth of Jackson (1958Jackson ( , 2004) ) and the dolomite CRT proposed by Gregg and Sibley (1984).Although we are confident that the criticisms of Gregg (2024) can be summarily dismissed with information and arguments presented in the original article by Ryan et al. (2023), we offer the following responses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".