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Record W2075249151 · doi:10.4018/ijgbl.2012010104

Martian Boneyards

2012· article· en· W2075249151 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Game-Based Learning · 2012
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArtifact (error)NarrativeEducational gameGame designComputer scienceGame DeveloperGame art designHuman–computer interactionMultimediaData scienceArtificial intelligenceArt

Abstract

fetched live from OpenAlex

This paper reports on research of a game designed for scientific inquiry in a new and publicly available massively-multiplayer online environment (MMO). Educators and game designers worked together to create a highly immersive environment, a compelling storyline, and research-grounded tools for scientific inquiry within the game. The designers also played characters within the game that allowed them to deliver an evolving and responsive game narrative while also serving as participant observers for the research. Researchers integrated these observations with survey data, log data, artifact review, and interviews, to provide a broad picture of the player experience and the gaming environment. This study provides evidence that sustained scientific inquiry can be nurtured in an MMO game and that gamers’ relationships with characters in the game and other players may help facilitate that inquiry.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.356
Teacher spread0.332 · 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