MétaCan
Menu
Back to cohort
Record W4400654567 · doi:10.1134/s1027451024700228

Impact Mill

2024· article· en· W4400654567 on OpenAlexaboutno aff
А. S. Аzhgalieva, D. N. Borisenko, N. N. Kolesnikov, А. А. Жохов

Bibliographic record

VenueJournal of Surface Investigation X-ray Synchrotron and Neutron Techniques · 2024
Typearticle
Languageen
FieldEngineering
TopicDiverse Industrial Engineering Technologies
Canadian institutionsnot available
FundersRussian Academy of Sciences
KeywordsPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

Abstract An impact mill has been developed to produce powders from shavings of refractory metals using the impact grinding method for reuse in electrometallurgy in devices with screw feed, for example, in 3D printers. The proposed device provides high uniformity of grinding with a minimum content of dust fraction and impurity content at low technical and economic costs. The result is achieved using a Laval nozzle, which operates in the supersonic jet formation mode. In the area of the first Mach disk, there are rod fenders arranged in a cascade, and the impact plate is located in the turbulence zone and is equipped with winglets with holes for separating crushed metal.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.013

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.

Opus teacher head0.015
GPT teacher head0.244
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Surface Investigation X-ray Synchrotron and Neutron TechniquesSame topicDiverse Industrial Engineering TechnologiesFrench-language works237,207