Bibliographic record
Abstract
The search for dark matter is one of the most interesting fields in physics, with groups at Queen’s and elsewhere working to detect concrete proof of its existence. The PICO collaboration has been developing and running experiments with bubble chambers for direct detection of dark matter for years, building several detectors leading up to its current project, PICO-500. This detector will contain a fiducial mass of 250kg of C3F8 and will search for weakly interacting massive particles (WIMPs), a promising candidate for dark matter. The active fluid is contained within two nested quartz jars installed inside a larger pressure vessel filled with hydraulic oil. With temperature constant, the hydraulics control the pressure within the jars and cause the liquid to become superheated. In this state, the deposition of energy by a WIMP interacting with the C3F8 within the vessel causes boiling. This creates a bubble with position and characteristics that can be observed and quantified. This summer, I worked with PICO’s engineering team on the design and construction of the pneumatic panel, the system that will supply pressurized air PICO-500’s valves and pressure accumulators. I made revisions and added details to the CAD models of the system, sourced parts and materials, and created engineering drawings to allow fabrication of components. As parts arrived, I assembled and adjusted the panel, ensuring physical components matched their 3D models. During downtime, I made drawings for other subsystems of PICO-500. I also assisted in the recommissioning of the Queen’s Test Chamber, a miniature bubble chamber used to test aspects of the PICO detectors in a more accessible environment. Future work will involve final assembly and testing of the valves, regulators and manifolds that make up the pneumatic panel, ensuring they are ready for installation.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".