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Institute of Food Technologists (IFT) Education Division Competition 2010 Winner: The Organic Price Tag

2011· article· en· W2040627694 on OpenAlexaff
Angie Che Yan Lam

Bibliographic record

VenueJournal of Food Science Education · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsActive listeningCompetition (biology)InterviewCore competencyPublic relationsPosition (finance)PsychologyMedical educationPedagogyPolitical scienceMarketingBusinessMedicine

Abstract

fetched live from OpenAlex

Abstract: One of the core competencies in the Institute of Food Technologists (IFT) Education standards is for students to achieve competency in communication skills (that is, oral and written communication, listening, interviewing, and so on). According to the IFT guidelines, by the time students graduate, they should not only be able to search for and condense information, but also be able to “communicate technical information to a nontechnical audience.” The Education Division of IFT sponsors a writing competition for undergraduate students to bring attention to and promote the development of communication skills. It has been shown that employees/entry‐level scientists who can communicate technical and nontechnical concepts succinctly will be in a better position to achieve management status after entering the work force. Monetary prizes are awarded to the authors of the top three papers. A revised version of the winning entry is published in the Journal of Food Science Education for dissemination to a world‐wide audience.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.167
Threshold uncertainty score0.560

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0090.002
Open science0.0020.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.1670.101

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 head0.050
GPT teacher head0.258
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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