Giant Feshbach resonances in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mmultiscripts><mml:mi mathvariant="normal">Li</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>6</mml:mn></mml:mrow></mml:mmultiscripts></mml:math>-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mmultiscripts><mml:mi mathvariant="normal">Rb</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>85</mml:mn></mml:mrow></mml:mmultiscripts></mml:math>mixtures
Bibliographic record
Abstract
We report on the observation of six large Feshbach resonances in a Fermi-Bose mixture of $^{6}\mathrm{Li}$ and $^{85}\mathrm{Rb}$ atoms. Near the resonances, both the elastic and inelastic collision rates are enhanced, and this results primarily in the loss of $^{6}\mathrm{Li}$ from an optical dipole trap since it is less massive and less confined than its $^{85}\mathrm{Rb}$ collision partner. We interpret our experimental data using a coupled-channels calculation which fully characterizes the ground-state scattering properties in any combination of spin states.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.075 | 0.007 |
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; both teacher heads agree on what is shown here.
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".