Addressing Dietary Fiber Terminology Consistency
Bibliographic record
Abstract
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.
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 | 0.081 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".