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Record W1482966524 · doi:10.1111/jfq.12065

Survey Reveals Urban Consumers' Attitudes and Beliefs Regarding the Use of Wax on Apples

2014· article· en· W1482966524 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Food Quality · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsAgriculture and Agri-Food Canada
FundersU.S. Food and Drug Administration
KeywordsDemographicsWaxingWaxEthnic groupMarketingAdvertisingOrder (exchange)PsychologyBusinessSociologyDemographyBiology

Abstract

fetched live from OpenAlex

Abstract This research explored consumers' awareness, attitudes and beliefs regarding the use of wax on apples, using a survey consisting of five demographic questions, 14 apple wax questions and five apple wax information statements. Consumers responded to queries regarding the use and nature of wax coatings, as well as any health and environmental concerns. They identified their preferred apple treatment ( unwaxed, waxed, either ) four times throughout the survey, after being presented with information. Consumers' responses were evaluated according to their demographics (age, gender and ethnicity). Statistical analyses (frequency plots, analysis of variance) were used to evaluate data from the two largest ethnic subgroups of consumers ( E uropean, A sian) ( n = 781). On average, consumers lacked knowledge and information about apple waxing. Interestingly, 84% of consumers initially stated they preferred unwaxed apples. While some 40% of consumers changed their preferences once additional information was provided, another 42.3% of consumers did not. Practical Applications This research successfully documented the attitudes and beliefs of urban consumers toward the use of wax on apples. It suggested some consumers might be more willing to accept waxed apples, if additional information (brochure or leaflet) was available, while others would not. As such, the research provided industry with objective information to assess the appropriateness of their marketing/retailing practices in order to meet the needs of their consumers.

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.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.109

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.277
Teacher spread0.178 · 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