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Record W2118118987 · doi:10.3968/7384

Virtual Satisfaction of Human With the Need in Attribute of Things

2015· article· en· W2118118987 on OpenAlexvenueno aff
Fang Ren, Zhang Ru-liang

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsnot available
Fundersnot available
KeywordsEmbodied cognitionObject (grammar)Computer scienceSwiftCharacter (mathematics)Human–computer interactionEpistemologyArtificial intelligenceAestheticsMathematicsPhilosophy

Abstract

fetched live from OpenAlex

In the real world, the entity and attributes of an object are unified. It is generally believed that inseparability of entity and attributes is fully embodied in the energy character of the object. Although entity and attributes are inseparable, it is likely to realize the relevant separation of entity and attributes by means of virtual reality technology (VRT). As a matter of fact, this kind of separation means relative separation of entity and attributes with virtual reality technology as the medium. This is of great significance as it enables people to get satisfied with their desire to perceive attributes of an object, and it is a way to satisfy people’s infinite desire by technology. With the swift progress of this technology, all kinds of limitations in the real environment successfully break through and the degree of human freedom is greatly improved.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.017
GPT teacher head0.222
Teacher spread0.205 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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