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Record W4379647204 · doi:10.31645/jisrc.23.21.1.4

Techy Tennis–A Game Beyond Reality

2023· article· en· W4379647204 on OpenAlexaff
Ayesha Anees Zaveri, Nabiha Faisal, Saba Imtiaz, Sarama Shehmir, Mobeen Nazar, Misbah Parveen

Bibliographic record

VenueJournal of Independent Studies and Research - Computing · 2023
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAugmented realityKey (lock)Object (grammar)Computer scienceFunction (biology)Human–computer interactionAtmosphere (unit)Enhanced Data Rates for GSM EvolutionMultimediaComputer graphics (images)Computer visionArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

The concept is to create a game based on augmented reality and use object tracking as the primary function for recognizing objects using a camera. The key goal is to design an atmosphere that not only satisfies a person's desire to play video games but also lowers their stress levels in a manner that is both cost-effective and makes less use of flashy devices and cutting-edge technology. The environment produced in this way will use a camera that can identify objects and carry out a series of activities that have been preset according to their functions.

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 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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.169
GPT teacher head0.456
Teacher spread0.287 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2023
Admission routes1
Has abstractyes

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