Probabilistic Surface Heat Flow Estimates Assimilating Paleoclimate History: New Implications for the Thermochemical Structure of Ireland
Bibliographic record
Abstract
Abstract Regions where surface temperature has increased since past glaciation events, such as Ireland, underestimate the heat output of the Earth unless paleoclimate corrections are applied. We apply probabilistic techniques to quantify the uncertainty of 22 paleoclimate‐corrected heat flow estimates in Ireland, which assimilate multiple surface temperature histories associated with 130 ka of glacial oscillation in the British Isles. Heat flow values increase by ∼15 mW/m2 after a paleoclimate correction and provide new insights into the thermochemical structure of the lithosphere. The heat flow regime is broadly delineated by the Iapetus Suture Zone that separates Laurentian to the north and Avalonian terranes to the south (mean surface heat flow of 73 ± 14 and 65 ± 14 mW/m2, respectively). The degree to which heat‐producing elements are partitioned into the uppermost crust is described by the differentiation index of a heat flow province. From Bayesian inversion, we determine that radiogenic elements are substantially more differentiated in the uppermost crust of Laurentia (DI=2.8 ± 1.4) than Avalonia (DI=1.5 ± 1.3), despite a moderately enriched lower crust (0.8 ± 0.3 μW/m3). This is facilitated by a thin yet highly radiogenic layer in the uppermost crust of Laurentia (3.9 ± 1.8 μW/m3). Extrapolating these results across the British Isles and Newfoundland suggests that heat‐producing elements have been more successfully reworked into the upper crust to the north of the Iapetus Suture Zone during continental accretion between Laurentia and Avalonia.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".