A model to calculate the viscosity of silicate melts
Bibliographic record
Abstract
Abstract Our recently developed model for the viscosity of silicate melts is extended to describe and predict the viscosities of oxide melts containing boron. The model requires three adjustable parameters to reproduce the viscosity of B 2 O 3 –SiO 2 melts and two parameters for each B 2 O 3 – M O x melt, where M O x is a basic oxide other than an alkali oxide. All available experimental data have been collected for binary melts formed by B 2 O 3 with SiO 2 , Al 2 O 3 , CaO, MgO, ZnO, PbO to calibrate the model. The viscosities of the B 2 O 3 -containing ternary and higher-order subsystems of the B 2 O 3 –CaO–MgO–PbO–ZnO–SiO 2 system and of the B 2 O 3 –CaO–MgO–PbO–ZnO–Al 2 O 3 system are then predicted by the model without any additional adjustable parameters. Experimental data were found for only five such subsystems: B 2 O 3 –PbO–SiO 2 , B 2 O 3 –CaO–SiO 2 , B 2 O 3 –PbO–ZnO, B 2 O 3 –PbO–Al 2 O 3 and B 2 O 3 –CaO–Al 2 O 3 . Predictions of the model are compared to these experimental data.
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 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 | 0.004 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".