Preparation and performance of energy-saving and environment-friendly autoclaved
Bibliographic record
Abstract
Quartz tailing sand (QTS) is a by-product of glass production, it's the fine sand obtained after quartz sand, the raw material of glass, had been crushed and screened, and its main chemical component is SiO 2 .In the float glass process, the harm of fine quartz sand lies in the fact that after entering the furnace, it will erode the refractory material, reduce the lifespan of the furnace, affect the uniformity of the batch, and block the channels between the checker bricks; and all these factors are not good for the glass production, therefore, the glass industry has stipulated requirements for the particle size of quartz sand as follows: the content of quartz sand with a particle size between 0.125 and 0.71 mm must be greater than 95%, and the content of quartz sand with a particle size smaller than 0.125 mm must be less than 5% [1].According to this proportion, during the glass making process, the quartzite will produce 30% QTS which can be used as the siliceous correction material for the dry-method cement production in the cement plants, but the actual application is quite insufficient.If the QTS has not been handled properly, it'll fly with the wind in dry seasons, causing desertification to the surrounding land, or it'll flow into the river with the rainwater during the rainy seasons, causing serious pollution to the environment, and meanwhile increasing the environmental protection burden of the manufacturing enterprises.The research on the comprehensive utilization of QTS in China is mainly focused on the production of chemical raw materials (white carbon black) [2], building materials (aerogels [3], cement [4,5], cera-Preparation and Performance of Energy-saving and Environment-friendly Autoclaved Aerated Concrete Prepared by Quartz Tailings Sand
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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 | 0.000 |
| 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 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".