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.
Bibliographic record
Abstract
Abstract Durability and reliability are necessary requirements for fuel cells to be introduced into the market place. However, activities necessary to meet these requirements are costly and time‐consuming. As a result, past experience and information is valuable and emphasis should be placed on ex situ and accelerated testing to minimize resource investment. In this contribution, gaps in knowledge are identified which could form the basis of further studies. The key components of performance degradation (kinetic, ohmic, mass transport) are briefly defined and provide a basis for the discussion on the sources of degradation (water management, impurities, reformate, materials, operating conditions, uniformity). Understanding of the factors affecting degradation leads to a discussion of possible mitigation strategies. Since the current state of the art is fragmentary and far from being comprehensive, further research efforts are required to clearly understand root causes, secondary effects and interactions in order to develop appropriate mitigation strategies for performance degradation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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 it