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
Economic barriers preventing commercialization of lignocellulose-toethanol bioconversion processes include the high cost of hydrolytic enzymes. One strategy for cost reduction is to improve the specific activities of cellulases by genetic engineering. However, screening for improved activity typically uses “ideal” cellulosic substrates, and results are not necessarily applicable to more realistic substrates such as pretreated hardwoods and softwoods. For lignocellulosic substrates, nonproductive binding and inactivation of enzymes by the lignin component appear to be important factors limiting catalytic efficiency. A better understanding of these factors could allow engineering of cellulases with improved activity based on reduced enzyme-lignin interaction (“weak lignin-binding cellulases”). To prove this concept, we have shown that naturally occurring cellulases with similar catalytic activity on a model cellulosic substrate can differ significantly in their affinities for lignin. Moreover, although cellulose-binding domains (CBDs) are hydrophobic and probably participate in lignin binding, we show that cellulases lacking CBDs also have a high affinity for lignin, indicating the presence of lignin-binding sites on the catalytic domain.
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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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