Simplified modeling of the impact of lithospheric-scale geological processes on thermal histories and low-temperature thermochronometers
Bibliographic record
Abstract
Abstract. Many geological processes influence or perturb the thermal state of the lithosphere. This presents a challenge for relating thermal history data modeled from thermochronometers such as apatite and zircon fission-track and (U-Th)/He dating to geological evolution, a primary goal of many thermochronology studies. Here we address this challenge by exploring the thermal and thermochronological evolution of tracked rock parcels in 1D models that simulate key lithospheric geological processes, including erosional exhumation, sedimentary burial and exhumation, dip-slip faulting and delamination of the lithospheric mantle. We compare results from common depth history scenarios in which the Moho either experiences exhumation/burial or remains at a fixed depth balanced by crustal flux and erosion. Results show that Moho depth changes have a significant effect on thermal histories and thermochronometers, though this is not often considered in thermal history studies. Further, our results show that the recorded response of thermal histories/thermochronometers in the upper crust and geological processes that disrupt the crustal thermal field may be disassociated in time, because of the time and length scales of different heat transfer mechanisms. For example, a delamination event produces younger thermochronometer ages than an identical crustal exhumation history without delamination, but younger ages do not record the timing of delamination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".