Ab initio study of low-dimensional metallic systems
Bibliographic record
Abstract
In the present Doctoral Thesis we gather all the research performed by the graduate student Jorge Botana Alcalde. Broadly speaking, the work consisted in the study of the structural, electrical and magnetic properties of a spread of low-dimensional systems, made up with transition metals. We can divide said systems in two categories: ultrathin film of iron and chromium, where the two iron layers are sandwiched around a central chromium layer, and atomic clusters, either made of gold or of an alloy of bismuth and manganese. This work was done using ab initio techniques, i.e. from first principles. In our systems that means to solve the non-relativistic Schrödinger equation for a many-electron system. Our approach to such a complex problem was by means of the density functional theory (DFT), which transforms the many-body problem, considering each electron interacting with every one of the other electrons, to a single-body problem, where each electron interacts only with an effective potential created by the electron density. The implementation of this approach for the calculation of our systems was performed using the deMon (density of Montreal) DFT software.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".