The Role of Momentum Partitioning in Covariance Ion Imaging Analysis
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Bibliographic record
Abstract
We present results from a covariance ion imaging study, which employs extensive filtering, on the relationship between fragment momenta to gain deeper insight into photofragmentation dynamics. A new data analysis approach is introduced that considers the momentum partitioning between the fragments of the breakup of a molecular polycation to disentangle concurrent fragmentation channels, which yield the same ion species. We exploit this approach to examine the momentum exchange relationship between the products, which provides direct insight into the dynamics of molecular fragmentation. We apply these techniques to extensively characterize the dissociation of 1-iodopropane and 2-iodopropane dications prepared by site-selective ionization of the iodine atom using extreme ultraviolet intense femtosecond laser pulses with a photon energy of 95 eV. Our assignments are supported by classical simulations, using parameters largely obtained directly from the experimental data.
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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