Prospectivo da Influência das Impurezas nas Propriedades do Cobre Refinado a Fogo (FRHC)
Bibliographic record
Abstract
Cobre refinado a fogo (FRHC) possui diversas aplicações, principalmente na produção de fios e cabos elétricos; metal com alto teor de impurezas, especialmente de oxigênio, cuja elevada concentração de impurezas pode afetar as propriedades do material. Dentre as propriedades, sobressai a alta condutividade térmica e elétrica. Este artigo tem como objetivo realizar uma prospecção científica e tecnológica sobre a influência das impurezas nas propriedades do cobre, a fim de compreender os efeitos provocados durante os processos de fabricação de fios e cabos. A metodologia utilizada é uma revisão bibliométrica, tomando como bases científicas Web of Science e ScienceDirect is Elsevier’s, para busca de artigos, e um mapeamento patentário na plataforma do EPO e Google Patents. Como resultados, 34 artigos e 13 patentes relacionadas, sendo perceptível nos últimos anos a falta de evolução e inovação de novos métodos e tecnologias de refino de cobre, principalmente voltados para a contenção de impurezas, com tendências China, Estados Unidos, Austrália, Polônia, Canadá, Reino Unido e Alemanha. Palavras-chave : Cobre (FRHC). Impurezas. Oxigênio. Propriedades. ABSTRACT Fire-refined copper (FRHC) has several applications, mainly in the production of electrical wires and cables; metal with a high content of impurities, especially oxygen, whose high concentration of impurities can affect the properties of the material. Among the properties, the high thermal and electrical conductivity stands out. This article aims to conduct a scientific and technological survey on the influence of impurities on copper properties. The methodology used is a bibliometric review based on Web of Science and ScienceDirect is Elsevier's scientific bases, to search for articles, and patent mapping on the EPO and Google Patents platform. As a result, 34 articles and 13 related patents were obtained, being noticeable in recent years, the lack of evolution and innovation of new methods and technologies for refining copper, mainly aimed at containing impurities, with trends in China, the United States, Australia, poland, canada. United Kingdom and Germany. Keywords : Copper (FRHC). Impurities. Oxygen. Properties.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".