Thermodynamic nexus between UNCBD and UNFCCC: Bounded openness over natural information and the Yasuní-ITT initiative
Bibliographic record
Abstract
<p class="15" align="justify"><span lang="EN-US" style="font-size: 10.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">Consilience of biodiversity and climate change is achievable through reduction to non-equilibrium thermodynamics. Subsequent construction supports a policy to decrease carbon emissions and species loss in capital-poor countries that are mega-diverse and carbon-rich. Incentives for conservation underpinned The Yasun&iacute;-ITT Initiative, whereby Ecuador sought payment not to drill for oil. The same logic holds for not opening highways in the Amazon. Consilience marries <em>Living within Limits</em> by Garrett Hardin with <em>Half<span style="color: black; mso-themecolor: text1;">-Earth</span></em><span style="color: black; mso-themecolor: text1;"> by E.O. </span>Wilson. Artificial Intelligence facilitates persuasion of the Conference of the Parties to the United Nations Framework Convention on Climate Change and the United Nations Convention on Biological Diversity.</span></p>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".