Dark matter search results from the PICO-60<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>CF</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:mrow><mml:mi mathvariant="normal">I</mml:mi></mml:mrow></mml:math>bubble chamber
Bibliographic record
Abstract
New data are reported from the operation of the PICO-60 dark matter detector, a bubble chamber filled with 36.8 kg of ${\mathrm{CF}}_{3}\mathrm{I}$ and located in the SNOLAB underground laboratory. PICO-60 is the largest bubble chamber to search for dark matter to date. With an analyzed exposure of 92.8 livedays, PICO-60 exhibits the same excellent background rejection observed in smaller bubble chambers. Alpha decays in PICO-60 exhibit frequency-dependent acoustic calorimetry, similar but not identical to that reported recently in a ${\mathrm{C}}_{3}{\mathrm{F}}_{8}$ bubble chamber. PICO-60 also observes a large population of unknown background events, exhibiting acoustic, spatial, and timing behaviors inconsistent with those expected from a dark matter signal. These behaviors allow for analysis cuts to remove all background events while retaining 48.2% of the exposure. Stringent limits on weakly interacting massive particles interacting via spin-dependent proton and spin-independent processes are set, and most interpretations of the DAMA/LIBRA modulation signal as dark matter interacting with iodine nuclei are ruled out.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".