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Bibliographic record
Abstract
A self-consistent model is developed for the surface and bulk states of thin ${\text{Y}}_{1\ensuremath{-}y}{\text{Ca}}_{y}{\text{Ba}}_{2}{\text{Cu}}_{3}{\text{O}}_{7\ensuremath{-}\ensuremath{\delta}}(\text{YCBCO})$ films. The dispersions of the chain and plane layers are modeled by tight-binding bands, and the electronic structure is then calculated for a finite-thickness film. The dopant atoms are treated within a virtual crystal approximation. Because YCBCO is a polar material, self-consistent treatment of the long range Coulomb interaction leads to a transfer of charge to the film surfaces, and to the formation of surface states. The tight-binding band parameters are constrained by the requirement that the calculated band structure of surface states at ${\text{CuO}}_{2}$-terminated surfaces be in agreement with photoemission experiments. The spectral function and density of states are calculated and compared with experiments. Unlike the case of ${\text{Bi}}_{2}{\text{Sr}}_{2}{\text{CaCu}}_{2}{\text{O}}_{8}$, where the surfaces are believed to be representative of the bulk, the densities of states at the YCBCO surfaces are shown to be qualitatively different from the bulk, and are sensitive to doping. The calculated spectral function agrees closely with both bulk-sensitive and surface-sensitive photoemission results, while the calculated density of states for optimally doped YCBCO agrees closely with tunneling experiments. We find that some density of states features previously ascribed to competing order can be understood as band structure effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.051 | 0.012 |
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".