Bibliographic record
Abstract
As one in a series of articles on Canadian contributions to mass spectrometry, this review begins with an outline of the history of accelerator mass spectrometry (AMS), noting roles played by researchers at three Canadian AMS laboratories. After a description of the unique features of AMS, three examples, (14)C, (10)Be, and (129)I are given to illustrate the methods. The capabilities of mass spectrometry have been extended by the addition of atomic isobar selection, molecular isobar attenuation, further ion acceleration, followed by ion detection and ion identification at essentially zero dark current or ion flux. This has been accomplished by exploiting the techniques and accelerators of atomic and nuclear physics. In 1939, the first principles of AMS were established using a cyclotron. In 1977 the selection of isobars in the ion source was established when it was shown that the (14)N(-) ion was very unstable, or extremely difficult to create, making a tandem electrostatic accelerator highly suitable for assisting the mass spectrometric measurement of the rare long-lived radioactive isotope (14)C in the environment. This observation, together with the large attenuation of the molecular isobars (13)CH(-) and (12)CH 2(-) during tandem acceleration and the observed very low background contamination from the ion source, was found to facilitate the mass spectrometry of (14)C to at least a level of (14)C/C ~ 6 × 10(-16), the equivalent of a radiocarbon age of 60,000 years. Tandem Accelerator Mass Spectrometry, or AMS, has now made possible the accurate radiocarbon dating of milligram-sized carbon samples by ion counting as well as dating and tracing with many other long-lived radioactive isotopes such as (10)Be, (26)Al, (36)Cl, and (129)I. The difficulty of obtaining large anion currents with low electron affinities and the difficulties of isobar separation, especially for the heavier mass ions, has prompted the use of molecular anions and the search for alternative methods of isobar separation. These techniques are discussed in the latter part of the review.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.027 |
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".