Semi-Automated Equipment for CO<sub>2</sub> Purification and Graphitization at the A.E. Lalonde AMS Laboratory (Ottawa, Canada)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract New computer-controlled, semi-automatic systems were designed and built for CO 2 purification and graphitization at the A.E. Lalonde Accelerator Mass Spectrometry (AMS) Laboratory with consideration for user friendliness and high throughput. The stainless steel vacuum lines are orbitally welded to ensure clean seams with low memory. The insulated graphitization ovens with plug-in electrodes provide a hazard-free environment for operators. The closed-loop cooling system circulating low-viscosity Dynalene at –40°C provides highly efficient water trapping. The LabVIEW TM software features (1) pressure and temperature recording for QA/QC; (2) safety interlocks to preclude operator errors resulting in sample loss, cross-contamination, or damaging a vacuum pump; and (3) automation for leak checking, iron conditioning, and running samples. Results from the first year of routinely measured standards, reference, and background materials are reproducible and within acceptance values. In the first year of operation (commissioned in spring 2014), over 1000 targets (~60% unknowns) were produced. With new tube sealing and CO 2 purification lines, and two more graphitization lines now operational, the Lalonde AMS Laboratory is able to provide routine radiocarbon analysis (>200 µg carbon) at a capacity of more than 7000 targets per year. Most importantly, the equipment is safe and intuitive, making it ideal for education and training students to run their own samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it