U-Pb Isotopic Data and Ages of Zircon and Titanite from Rocks from the Yukon-Tanana Upland, Alaska
Bibliographic record
Abstract
This data set contains 3 tables containing uranium-lead (U-Pb) isotopic data and crystallization ages of zircon and titanite from igneous, metamorphic, and sedimentary rocks collected from the Yukon-Tanana upland of eastern interior Alaska between 2013 and 2019. Bulk samples of igneous and metamorphic rocks were processed into concentrated mineral separates of zircon and (or) titanite in USGS laboratories in Denver, Colorado, or by Apatite to Zircon, Inc. (A2Z) and analyzed by USGS research scientists at the Stanford-USGS Sensitive High Resolution Ion Microprobe with Reverse-Geometry (SHRIMP-RG) at Stanford University. Bulk samples of sedimentary and metasedimentary rocks were processed into concentrated mineral separates of detrital zircon and analyzed by Apatite to Zircon, Inc. and GeoSep Services (GSS) using laser-ablation-inductively-coupled-plasma-mass spectrometry (LA-ICP-MS) techniques. The 2 data tables ("geochronology_detritalZircon_yukonTananaUpland_jones.csv"; "geochronology_SHRIMP-RG_yukonTananaUpland_jones.csv") accompanying this data release report the isotopic composition of uranium (U) and thorium (Th) measured in each grain, ratios of two isotopes of lead (207Pb and 206Pb) and two isotopes of uranium (235U and 238U), and the age of each grain. A third table ("geochronology_sampleSummary_yukonTananaUpland_jones.csv") reports sample locations, rock characteristics, and interpreted ages. The SHRIMP-RG data table ("geochronology_SHRIMP-RG_yukonTananaUpland_jones.csv") also reports concentrations of selected trace elements measured in each grain.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".