Effect of postglacial warming seen in high precision temperature log deep into the granites in NE Alberta
Bibliographic record
Abstract
now verify this estimate in this paper based on new information on heat production and thermal conductivity.We also attempt to reconstruct surface paleotemperature history for the last 100 kyr from functional space inversion (FSI) of the thermal data. Borehole temperature logs paleoclimatologyThe method how to reconstruct surface temperature history from inversions of precise temperature logs done in wells was pioneered earlier by Čermák (1971) and by Lachenbruch and Marshall (1986); (see: Bodri and Čermák 2007 for review and list of references on the subject).The method is based on the inversion of stabilized, high precision deep borehole temperature logs, which are in thermal equilibrium with surrounding rock.Deep down to some 2-km depth perturbation of the heat flow could be caused by warming since recent glaciations ending some 12-13 kyr ago in Canada (Ritchie 1983).Surface temperatures peaked in the Holocene Optimum 6-7 kyr ago known to be some 1-2 °C warmer than recent centuries temperature level (Kerwin et al. 1999).Perturbations observed down to 0.1-0.3km are mainly related to the climate changes of the last 1-2 centuries (Pollack et al. 1998;Bodri and Čermák 2007;Rath et al. 2012) on large regional and continental scale.All these surface temperature changes influence the subsurface heat flow.The method has been applied to reconstruct timing and amplitude of surface temperature change from latest glacial to postglacial climatic history through many areas in Eurasia and North America (Hotchkiss and Ingersoll 1934;
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".