Supporting a Resilience Observatory to Climate Risks in French Polynesia: From Valorization of Preexisting Data to Low-Cost Data Acquisition
Bibliographic record
Abstract
Climate change has an ever-increasing impact on island territories. Whether it is due to rising sea levels or the increase in recurrence and intensity of extreme events, island territories are increasingly vulnerable. These impacts are expected to affect marine and terrestrial biodiversity, human occupation (infrastructure) and other activities such as agriculture and tourism, the two economic pillars of French Polynesia. While the current and future impacts of climate change on island territories are generally accepted, data acquisition, modeling, and projections of climate change are more complex to obtain and limitedly cover the island territories of the Pacific region. This article aims to develop methodologies for the acquisition and exploitation of data on current and future climate risks and their impacts in French Polynesia. This work of acquisition and valorization is part of a research project for the development of an observatory of resilience to climate risks in the perspective of building a spatial decision support system.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".