Bibliographic record
Abstract
According to aerodynamics,plasma spray theory and the idea of expert in one thing and good at many ,multi-functional microplasma spraying systems were developed.The IGBT inversion technology,micro-computer control engineering,soft switch technology,Laval nozzle structure and center axial powder feed were adopted in the designs of micro-plasma spraying systems,which made it possess the characteristics of small volume,light weight,strong anti-jamming,accurate control,high velocity of spray particles,high deposit efficiency of powder and high reliability etc.The system can produce different kinds of high quality coatings.The experimental results show that the bonding strength and microhardness of nano-structured Al_2O_3+13%TiO_2 coatings produced by multi-functional micro-plasma spraying are better than those of the same coatings produced by 9M plasma spraying.As the result,the coatings whose properties are equavitent of those of the coatings produced by conventional plasma spraying can also be deposited by multi-functional micro-plasma spraying with lower power by means of improving power design,spray gun structure and powder feed method.
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 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".