Bibliographic record
Abstract
<!--HTML--> <span><span>Self-organization of the systems follows the complexity of its structural configuration, and is the ultimate feature that allows the system to survive, adapt and evolve. What is the principle that rules how self-organization works? In this lecture, I will introduce what is sometimes called “the 4th principle of thermodinamics”, that is, the Maximum Empower Principle, which follows the same line of reasoning that addressed the maximization of power as the driving force for living systems organization. The empower, that is the flow of emergy characterizing a system operation, is addressed as the real quantity which a system maximizes in its operation and evolution. In particular, self-organization tends to develop network connections that use energy resources -and so emergy- in feedback actions to aid the process of getting more resources or using them more efficiently.</span></span> <span><span><strong>Francesco Gonella short bio</strong><br /> PhD in Physics at University of Padova, Italy. Excéllence Postdoctorale at the Université Laval, Québec City, Canada. Since 2016, Full Professor of Physics at the Department of Molecular Sciences and Nanosystems of the Ca’ Foscari University of Venice. After twenty years of activity as an experimental physicist (study of nanostructured glasses, artistic glasses and glasses for energy technologies), ten years ago I have shifted my interests to Systems Thinking and Emergy Analysis, applied to the study of the functioning and the integrated sustainability of systems. I am Director of the “International School on Emergy Accounting'', and member of the Executive Council of the International Society for the Advancement in Emergy Research. I teach Sustainability and Systems Thinking at the Beijing Normal University in China as a high-end foreign expert, and keep courses on the same topics at the Universities of Turin and Catania in Italy. I was Visiting Professor at Tokyo Institute of Technology, Japan, for two years, and Visiting Researcher at Vanderbilt University (Nashville, USA) and the University of Florida (Gainesville, USA). H-index=37 (2020, Scopus). Author or co-author of almost 200 publications in international peer-reviewed Journals. Invited lecturer in Universities in Canada, USA, Germany, India, Japan, China, Poland, France.</span></span>
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.229 | 0.005 |
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".