Phanerozoic tectonic and sedimentation history of the Arctic: constraints from deep-time low-temperature thermochronology data of Ellesmere Island and Northwest Greenland
Bibliographic record
Abstract
We present thermochronology and geochronology data from basement and (meta-)sedimentary samples collected on Ellesmere Island (Canadian High Arctic) and Northwest Greenland. The interpretations of our data are described and discussed in a paper in the journal Tectonics, titled “Phanerozoic tectonic and sedimentation history of the Arctic: constraints from deep-time low-temperature thermochronology data of Ellesmere Island and Northwest Greenland”. Our data include apatite fission track analyses, apatite (U-Th-Sm)/He analyses, and U-Pb analyses of detrital zircons. The data were used for inverse Monte Carlo simulations for obtaining time-temperature histories. We include descriptions of the analytical details related to the measurements, tests for potential effects of radiation damage on the (U-Th-Sm)/He age distributions, and we display the results of the Monte Carlo simulations for the individual samples. Our data set comprises a table summarizing constraints and specific parameters used for simulations (Table S1, summary input modelling), a table displaying the results of the simulations (Table S2, summary outcome thermal history inversions), a table displaying calculations of modelled overburden (Table S3, calculation of net burial and exhumation), a table summarizing the results of apatite fission track data, followed by several tables with the single-grain age and length data of fission track analyses (Table S4), a table with the detailed results of apatite (U-Th-Sm)/He thermochronology (Table S5), a table with single-grain zircon U-Pb data (Table S6), and a table with the results of statistical analysis for distinguishing individual age groups from the detrital zircon U-Pb age distributions (Table S7).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".