Bibliographic record
Abstract
Summary form only given. Although most laboratory plasmas are produced from heating of solids, little is known about the properties of the intervening states during evolution of a cold solid into hot plasma. Such states lie in the so-called Warm Dense Matter regime where temperature is comparable to Fermi energy and density is sufficiently high to render the ions strongly coupled. Experimental studies of Warm Dense Matter are challenging due to extreme pressure (~Mbar) of the states while theoretical studies are greatly complicated by the interplay of electronic excitation, electron degeneracy, and strong ion-ion correlation effects. Nonetheless, since its emergence in 1999 Warm Dense Matter has been rapidly gathering interest. This is driven by the fundamental significance of understanding the convergence of condensed matter and plasma physics as well as the relevance of Warm Dense Matter to broad areas including material science under extreme conditions, inertial confinement fusion, and planetary physics. Advances in Warm Dense Matter research are being propelled simultaneously by (i) ready availability of intense energy sources including lasers, free electron lasers, X-rays and energetic particles (electron and ion), and (ii) increasing capability in ab-initio molecular dynamic simulations. In this talk I will begin with a brief introduction to Warm Dense Matter. This will be followed by discussions on our earlier studies of electron-ion coupling, AC conductivity and solid-plasma transition in Warm Dense Matter states with energy density of ~10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sup> J/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".