Dataset of photoemission valence-band mapping and band reconstruction of 2H-WSe2
Bibliographic record
Abstract
Photoemission band mapping, band structure calculation, and reconstructed band dispersion of layered semiconductor 2H-WSe2, a type of 2D transition metal dichalcogenide. Provenance: The experimental data were measured using the SPECS METIS 1000 3D detector with extreme UV pulses centered at 21.7 eV as the photoemission light source. The samples were commercially purchased and directly used in the experiment. The calculated data were converted and preprocessed from an existing record (http://dx.doi.org/10.17172/NOMAD/2020.03.28-1), which contains the band structure of 2H-WSe2 calculated using density functional theory (DFT) at the level of LDA, PBE, PBEsol, and HSE06 exchange-correlation functionals using FHI-aims (version 171221_1). Content: The data contain binned and preprocessed photoemission data; Preprocessed DFT calculations used for initializing the band reconstruction; Postprocessed band reconstruction data (including 14 identifiable valence bands). Usage: The dataset may be used for reproducing the results in (https://arxiv.org/abs/2005.10210), computational benchmarks or separately for other materials science applications. For reconstruction, see the source code and examples on GitHub (https://github.com/mpes-kit/fuller).
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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) | 0.002 | 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 | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".