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Record W4404228943 · doi:10.1097/nt.0000000000000719

Addressing Dietary Fiber Terminology Consistency

2024· article· en· W4404228943 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

VenueNutrition Today · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgricultural Research ServiceInstitute for the Advancement of Food and Nutrition SciencesNational Academies of Sciences, Engineering, and MedicineU.S. Department of Agriculture
KeywordsTerminologyConsistency (knowledge bases)Dietary fiberFiberComputer scienceFood scienceChemistryMaterials scienceArtificial intelligencePhilosophyLinguisticsComposite material

Abstract

fetched live from OpenAlex

The Dietary Fiber (fiber) Terminology Roundtable was organized to address crucial issues concerning current definitions of dietary fiber and the pressing need to resolve inconsistencies and ambiguities in fiber terminology. This publication captures valuable insights and diverse perspectives from a multidisciplinary group of experts who span research areas, including fiber and carbohydrate research in human health, fiber analysis and methodology, and food and nutrition ontology development and application, as well as food composition data and public health. Although health is a critical concern, the use of the word "health" here is directly tied to its intrinsic role in regulatory definitions of dietary fiber. The presentations supported the view of dietary fiber as an essential food component with significant potential to improve health, underscoring the need for clarity in language and communication. Additionally, the concept of a systematic ontological framework was introduced as a highly valuable and most suitable solution to facilitate clear communication about fiber in research, education, healthcare, and industry. As a result, a Dietary Fiber Ontology Working Group has been formed, and the collective expertise within the group will contribute to the creation of an open-access fiber ontology. This effort aims to not only address educational aspects but also support the identification of fiber-related health outcomes and the underlying mechanisms responsible for biological effects.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.039
GPT teacher head0.302
Teacher spread0.264 · 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