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Record W2127208870 · doi:10.5539/jfr.v1n4p150

Sensorial Characteristics of a Senescent Plantain Empiric Dish (Dockounou) Produced in Côte d’Ivoire

2012· article· en· W2127208870 on OpenAlexvenueno aff
Akoa Essoma Edwige Flore, Kra Kouassi Aboutou Séverin, Mégnanou Rose-Monde, Akpa Eric Essoh, Ahonzo Niamké L. Sébastien

Bibliographic record

VenueJournal of Food Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCote d ivoireTasteEthnic groupFlavorGeographyAge groupsFood scienceDemographyBiologyArtHumanitiesSociologyAnthropology

Abstract

fetched live from OpenAlex

Dockounou, a plantain derivate dish, is proposed on Côte d’Ivoire markets, under various sensorial qualities. Nevertheless, most of time, consumers’ demands are not satisfied. Hence, a survey was undertaken in Abidjan to determine dockounou consumers’ preferential sensorial criteria, for further improvements. 1250 respondents of both genre, from three age categories (junior, major and senior), literates or not and belonging to all the ethnic groups of Côte d’Ivoire, were interviewed through the whole communes. Among the eight sensorial criteria of dockounou, the majority of respondents identified packaging (98.16%), structure (94.47%), taste (91.11%) and the color (80.13%) as the first essential sensorial criteria for the choice of dockounou. They were followed by the texture (74.29%), flavor (68.43%), cooking mode (66.59%) and the type of flour (59.05%). The specific sensorial characteristics most of the respondents expected, independently to the socio-demographic variables, were <em>Thaumatococcus daniellii</em> leaf (55.59%) as packaging, smooth structure (58.44%), sweet-spiced taste (80.65%), brown color (67.32%), hard texture (57.31%), plantain flavor (73.96%), water cooking (48.08%) and maize (38.24%) and rice (37.09%) flours. However, these sensorial characteristics choices were significantly influenced by the ethnic and the age category more than the genre and the education.<br />

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.148
GPT teacher head0.364
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2012
Admission routes1
Has abstractyes

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