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Record W3117217668 · doi:10.32370/ia_2020_12_5

Innovative Design of Equipment and Tools. Innovative Systems with Elements of Artificial Intelligence and Neural Networks

2020· article· en· W3117217668 on OpenAlexvenueno aff
Dmitrii Shekhovtsov

Bibliographic record

VenueIntellectual Archive · 2020
Typearticle
Languageen
FieldEngineering
TopicEngineering Technology and Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)Production (economics)Order (exchange)Computer scienceSet (abstract data type)Engineering managementManufacturing engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

A set of new and rather unusual conditions and requirements for all stages of design, pre- production and complex production itself, which aims to create the capabilities and specifics of so-called smart production, machines, transport, technologies and smart jobs in all industries, medicine, science, training of specialists and agriculture, make us reconsider the existing order of things and search for new organizational and technical solutions aimed at ensuring compliance with the newly emerged conditions. The author of the publication considers it important to consider this as a model within the sector of the technological field of medical equipment and its accompanying materials and technologies.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.108
GPT teacher head0.270
Teacher spread0.162 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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