Novel valorization of Sargassum´s extracts and post-extraction residual materials as sources of bioactive extracts and natural products, of precursors for materials preparation, of activated carbons and mineral additives
Bibliographic record
Abstract
Today, substantial amounts of pelagic Sargassum algae beach along the Caribbean basin. The objective of this research is the exploration of the two main species of Sargasum present in Guadeloupe (Sargassum natans and Sargassum fluitans) as a source of natural products, and innovative biomaterials. The first part of this work was focused on the methodological study of extractive treatment of both species of Sargassum. Several successive extractions were explored, working with three organic solvents hexane, dichloromethane and methanol, two different extractive times (24 and 48 hours), and at two temperatures (room temperature and solvent reflux temperature). The analysis of the relevance of each parameter was analyzed. A metabolomic study, on targeted analyses of the polyphenolic content was developed in collaboration with the team of Professor David Wishard (TMIC laboratory, University of Alberta, Canada), identifying the presence of several natural polyhenols in both species. The study of the antioxidant is in progress in collaboration with the team of Professor Remi Neviere (Cardiopulmonary Functional Explorations) at the Centre Hospitalier Universitaire from Martinique. In parallel, the extraction of alginates from the extractive residues was achieved, obtaining these natural polymers with an overall good yield. Finally the algae residues post extraction was explored to developed innovative potential applications, as for example the production of active charcoal or mineral additives for geopolymeric materials.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".