Production Methods and Physicochemical Characteristics of Cassava Inoculum and Attiéké from Southern Côte d’Ivoire
Bibliographic record
Abstract
Attiéké is a food from Côte d’Ivoire exported today in several countries. For evaluating production processes, determinant factors and quality attributes of attiéké, a production survey and a physicochemical study were carried out. The survey included 170 producers from the departments of Abidjan, Dabou and Jacqueville, major production areas. Traditional attiéké (Adjoukrou, Ebrié, Alladjan) and a commercial type Garba were investigated for physicochemical analyses. The cassava variety (98% of producers) had no effect on traditional cassava inoculum but had an impact on attiéké quality. The step of fermentation is necessary. The difference between studied attiéké related to microflora of inoculum whose identification may provide adequate explanations on the product. Respect for the various steps of manufacturing process is also essential. Physicochemicals confirmed observed differences between attiéké types. Organoleptic characteristics are criteria of differentiation between attiéké. The quality of preference is well-made grains without fibers. The results obtained also highlighted the risks faced by regular consumers of Garba due to its high cyanide content (12 mg/100g MS) compare to other attiéké (4.41 mg/100g MS).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".