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 Size enlargement concerns those processes that bring together fine powder particles into larger masses to improve the properties of the powders. Many diverse industries benefit from size enlargement processes. Examples discussed herein include fertilizer granulation, iron ore pelletization, tablet feeds for pharmaceuticals, instant food products, and the processing of mineral and chemical products. This article primarily considers those processes in which the creation of coarse granular material from fines is the objective. The characteristics of individual agglomerates are important only in their effect on the properties of the bulk granular product. Following an initial discussion of particle‐bonding mechanisms and the theory and measurement of agglomerate strength, size enlargement processes and equipment, including principal design parameters, are described. These processes are considered on the basis of the principal mechanism used to bring the particles together into agglomerates. The categories used are agglomeration by tumbling and other agitation methods, pressure compaction and extrusion methods, heat reaction, fusion, and drying methods, and agglomeration from liquid suspensions by competitive wetting.
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) | 0.001 | 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) | 0.001 | 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