GGR Critical Review of Analytical Developments in 2004–2005
Bibliographic record
Abstract
In 2005 Geostandards and Geoanalytical Research embarked upon a new initiative for its readers. Key researchers in various fields of geoanalytical technique development and their application were identified and invited to provide reviews pertinent to their expertise. As noted in the first of these publications “…instead of revisiting the historical context or decades of development in each analytical technique, the goal here has been to capture a snapshot of “hot topics” across a range of fields as represented in the… literature” (Hergt et al. 2005). Rather than prepare an annual review, a decision was taken earlier this year to provide a biennial summary of progress and accomplishments, in this case for the years 2004–2005. The principal techniques employed in Earth and environmental sciences are covered here, and include laser ablation and multicollector ICP‐MS, ICP‐AES, thermal ionisation and secondary ion mass spectrometry, as well as neutron activation analysis, X‐ray fluorescence and atomic absorption spectrometry. A comprehensive review of the development of reference materials, often essential to these techniques, is also provided. The contributions assembled serve both to keep readers informed of advances they may be unfamiliar with, but also as a means of showcasing examples of the breadth and depth of work being conducted in these fields.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".