Bibliographic record
Abstract
Abstract Thermodynamics gives rise to a number of conceptual issues that have been explored by both physicists and philosophers. One source of contention is the nature of thermodynamics itself. Is it what physicists these days would call a resource theory, that is, a theory about how agents with limited means of manipulating a physical system can exploit its physical properties to achieve desired ends, or is it a theory of the basic properties of matter, independent of considerations of manipulation and control? Another source of contention is the relation between thermodynamics and statistical mechanics. It has been recognized since the 1870s that the laws of thermodynamics, as originally conceived, cannot be strictly correct. Because of fluctuations at the molecular level, processes forbidden by the original version second law of thermodynamics are continually occurring. The original version of the second law is to be replaced with a probabilistic version, according to which large-scale violations of the original second law are not impossible but merely highly improbable, and small-scale violations unpredictable, unable to be harnessed to systematically produce useful work. The introduction of probability talk raises the question of how we should conceive of probabilities in the context of deterministic physical laws.
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 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".