Collision strength and effective collision strength for Br XXVII
Bibliographic record
Abstract
Collision strengths for all 1326 transitions among lowest 52 fine-structure levels of Br XXVII have been computed using Dirac atomic R-matrix code (DARC). Resonances in the threshold region have been completely resolved and the contributions of these resonances to allowed and forbidden transitions have been presented. The partial collision strength for each angular momentum has been studied graphically. Effective collision strengths have also been determined within the temperature range for all 1326 transitions among the lowest 52 levels. Target state energies of the lowest 52 fine-structure levels have been computed from the multi-configuration Dirac–Fock method (MCDF). Additionally, similar calculations with the relativistic distorted wave method and flexible atomic code (FAC) have also been performed to check the accuracy of our results. The present work represents a new and significant work with improvement in the field. We believe that our presented data of collision and effective collision strengths may be useful in the future for benchmark calculations and for plasma diagnostics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".