`Making the molecular movie': first frames
Bibliographic record
Abstract
Recent advances in high-intensity electron and X-ray pulsed sources now make it possible to directly observe atomic motions as they occur in barrier-crossing processes. These rare events require the structural dynamics to be triggered by femtosecond excitation pulses that prepare the system above the barrier or access new potential energy surfaces that drive the structural changes. In general, the sampling process modifies the system such that the structural probes should ideally have sufficient intensity to fully resolve structures near the single-shot limit for a given time point. New developments in both source intensity and temporal characterization of the pulsed sampling mode have made it possible to make so-called 'molecular movies', i.e. measure relative atomic motions faster than collisions can blur information on correlations. Strongly driven phase transitions from thermally propagated melting to optically modified potential energy surfaces leading to ballistic phase transitions and bond stiffening are given as examples of the new insights that can be gained from an atomic level perspective of structural dynamics. The most important impact will likely be made in the fields of chemistry and biology where the central unifying concept of the transition state will come under direct observation and enable a reduction of high-dimensional complex reaction surfaces to the key reactive modes, as long mastered by Mother Nature.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.235 | 0.101 |
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".