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Record W2343315898 · doi:10.5539/jmsr.v5n3p52

Development of New Structural Materials with Improved Mechanical Properties and High Quality of Structures through New Methods

2016· article· en· W2343315898 on OpenAlex
Salokhiddin D. Nurmurodov, A. K. Rasulov, Nodir Turakhodjaev, Kudratkhon Bakhadirov, Lazizkhan Yakubov, K. P. Abdurakhmanov, Tokhir Tursunov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Materials Science Research · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceDurabilityMachinabilityAlloyMetallurgyRefractory metalsTungstenCharacterization (materials science)Wear resistanceProcess engineeringComposite materialNanotechnologyMachining

Abstract

fetched live from OpenAlex

<p class="1Body">Up-to-date science and technology requires further development and wide introduction of new high- performance processes to produce refractory metals. These may include plasma chemical technology of high dispersed powders production. Practical implementation of plasma chemical method in producing and processing of high dispersed powders is in its initial stage. Along with this at the present time the demand for processing of structural materials with improved physical and mechanical properties is now steadily increasing. Such materials have low machinability due to high hardness and durability at high temperatures which results in heavy wear of a cutting tool. To improve the efficiency when processing hard-to-cut materials it is necessary to enhance the tool’s durability; this can be provided by application of new grades of hard alloys received from tungsten nanopowders. New alloy, obtained by the new developed technology, has higher degree of hardness and wear resistance compared with existing alloys and will be intended for hard materials processing.</p>

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.150
GPT teacher head0.421
Teacher spread0.271 · 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