X-ray diffraction data of 96 Na-ion cathodes both before and after accelerated aging.
Bibliographic record
Abstract
96 XRD patterns are included in this dataset. They were all collected using Mo radiation, but the scattering angles have been converted to those of Cu k-alpha,1. There are two subfolders: the first has pristine materials, while the other has the data for samples after aging in humid air. In each subfolder the sample lists are: 1a Na0.66MnO2 2a Na0.66Fe0.1Mn0.9O2 3a Na0.66Fe0.3Mn0.7O2 4a Na0.66Fe0.5Mn0.5O2 5a Na0.9Fe0.5Mn0.5O2 6a Na0.9Fe0.6Mn0.4O2 7a NaFe0.7Mn0.3O2 8a NaFe0.8Mn0.2O2 9a Na0.66Fe0.4Mn0.5Ti0.1O2 10a Na0.66Fe0.4Ni0.1Mn0.5O2 11a Na0.66Fe0.1Ni0.4Mn0.5O2 12a Na0.66Ni0.1Mn0.9O2 13a Na0.66Ni0.33Mn0.66O2 14a Na0.66Ni0.33Mn0.66O2 15a Na0.66Ni0.33Mn0.66O2 16a NaNi0.5Mn0.5O2 17a NaNi0.5Mn0.5O2 18a Na0.66Co0.1Mn0.9O2 19a Na0.66Co0.3Mn0.7O2 20a Na0.66Cu0.1Mn0.9O2 21a Na0.66Cu0.3Mn0.7O2 22a Na0.66Ni0.3Mn0.6Ti0.1O2 23a Na0.66Ni0.35Ti0.65O2 24a Na0.66Ni0.1Cu0.1Fe0.1Co0.2Ti0.2Mn0.3O2 1b Na0.66Li0.1Mn0.9O2 2b Na0.66Li0.1Fe0.1Mn0.8O2 3b Na0.66Li0.1Fe0.2Mn0.7O2 4b Na0.66Li0.1Fe0.4Mn0.5O2 5b Na0.9Li0.1Fe0.4Mn0.5O2 6b Na0.9Li0.1Fe0.5Mn0.4O2 7b NaLi0.1Fe0.6Mn0.3O2 8b NaLi0.1Fe0.7Mn0.2O2 9b Na0.66Li0.1Fe0.3Mn0.5Ti0.1O2 10b Na0.66Li0.1Fe0.3Ni0.1Mn0.5O2 11b Na0.66Li0.1Fe0.1Ni0.3Mn0.5O2 12b Na0.66Li0.1Ni0.1Mn0.8O2 13b Na0.66Li0.1Ni0.23Mn0.66O2 14b Na0.66Li0.1Ni0.33Mn0.56O2 15b Na0.66Li0.1Ni0.3Mn0.6O2 16b NaLi0.1Ni0.4Mn0.5O2 17b NaLi0.1Ni0.45Mn0.45O2 18b Na0.66Li0.1Co0.1Mn0.8O2 19b Na0.66Li0.1Co0.3Mn0.6O2 20b Na0.66Li0.1Cu0.1Mn0.8O2 21b Na0.66Li0.1Cu0.2Mn 0.7O2 22b Na0.66Li0.1Ni0.2Mn0.6Ti0.1O2 23b Na0.66Li0.1Ni0.25Ti0.65O2 24b Na0.66Li0.1Ni0.1Cu0.1Fe0.1Co0.1Ti0.2Mn0.3O2
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".