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 B2O3–SiO2 melts and two parameters for each B2O3–MO x melt, where MO x is a basic oxide other than an alkali oxide. All available experimental data have been collected for binary melts formed by B2O3 with SiO2, Al2O3, CaO, MgO, ZnO, PbO to calibrate the model. The viscosities of the B2O3-containing ternary and higher-order subsystems of the B2O3–CaO–MgO–PbO–ZnO–SiO2 system and of the B2O3–CaO–MgO–PbO–ZnO–Al2O3 system are then predicted by the model without any additional adjustable parameters. Experimental data were found for only five such subsystems: B2O3–PbO–SiO2, B2O3–CaO–SiO2, B2O3–PbO–ZnO, B2O3–PbO–Al2O3 and B2O3–CaO–Al2O3. Predictions of the model are compared to these experimental data.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".