GEOTRACES intercalibration of <sup>230</sup>Th, <sup>232</sup>Th, <sup>231</sup>Pa, and prospects for <sup>10</sup>Be
Bibliographic record
Abstract
Nineteen labs representing nine nations participated in the GEOTRACES intercalibration initiative that determined concentrations of 232 Th, 230 Th, 231 Pa, or 10 Be in seawater, suspended particles or sediments. Results generally demonstrated good agreement among labs that analyzed marine sediments. Two sets of seawater samples, aliquots of particulate material filtered in situ, and/or aliquots of biogenic sediments were distributed to participating labs. Internal consistency among participating labs improved substantially between the first and second set of seawater samples. Contamination was a serious problem for 232 Th. Standard Niskin bottles introduced no detectable contamination, whereas sample containers, reagents, and labware were implicated as sources of contamination. No detectable differences in concentrations of dissolved 232 Th, 230 Th, or 231 Pa were observed among samples of seawater filtered through Nuclepore, Supor, or QMA (quartz) filters with pore diameters ranging between 0.4 and 1.0 µm. Isotope yield monitors equilibrate with dissolved Th in seawater on a time scale of much less than 1 day. Samples of filtered seawater acidified to a pH between 1.7 and 1.8 experienced no detectable loss of dissolved Th or Pa during storage for up to 3 years. The Bermuda Atlantic Time Series station will serve as a GEOTRACES baseline station for future intercalibration of 232 Th and 230 Th concentrations in seawater. Efforts to improve blanks and standard calibration are ongoing, as is the development of methods to determine concentrations of particulate nuclides, tests of different filtration methods, and an increasing awareness of the need to define protocols for reporting uncertainties.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".