FRBR implementation and user research
Bibliographic record
Abstract
Abstract The IFLA Functional Requirements for Bibliographic Records (FRBR) conceptual model, published in 1998, focuses on the representation of the bibliographic universe, using an entity‐relationship model []. It has direct and great impact to the whole area of knowledge organization, especially the description, access, and sharing of bibliographic resources. As a conceptual model, FRBR is subject to various interpretations and implementations. This panel will focus on practical aspects of FRBR and related user studies: FRBR model validation, FRBR user research, FRBR/FAO model implementation and benefits, and RDA vocabulary developments based on FRBR.
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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 | 0.436 | 0.456 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.013 | 0.015 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.014 |
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".