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Record W7006122622

St. John's University - IdeaSquare Planet Pilot

2024· other· en· W7006122622 on OpenAlexaboutno aff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2024
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCrewResource (disambiguation)Settlement (finance)Selection (genetic algorithm)On boardGovernment (linguistics)Game design
DOInot available

Abstract

fetched live from OpenAlex

If you were to travel to an exoplanet, how would your crew manage their resources? A board game developed by students at IdeaSquare aims to tackle this question with fun thought experiments and quick decision-making! Inspired by our upcoming educational endeavour, IdeaSquare Planet, game design students from St. John’s University in New York came for an intense week at CERN to develop a board game based on the setting of travel to an exoplanet. They decided to centre their game on resource management, a decisive aspect of our educational programme which aims to make people think about the big questions of the future to better reflect on the present. Their game is divided into several phases, using some of the modules from IdeaSquare Planet. Thus, a preparation phase for the travel is devoted to the selection of the crew, the expertise necessary to reach the destination, but also the organisation and decision-making system (democratic, authoritarian, representative, etc.). Then, the ship takes off and begins a long journey towards the unknown planet. This journey is of course not without obstacles and the crew will have to make quick and potentially costly decisions to deal with unexpected situations that arise. Finally, when the pale dot of the planet hanging in the cosmos has grown sufficiently and it is time to settle there, the establishment of the settlement and its proper functioning brings new challenges which give rise to gameplay still a little different. Players will need to complete a certain number of rounds to win this collaborative game. Many people from the IdeaSquare team and the CERN community volunteered to playtest multiple iterations of the game over the days, with it improving with feedback from each team of players. The students did an impressive job and initiated a collaborative effort to arrive at a version that best represents the IdeaSquare Planet philosophy. IdeaSquare Planet is an educational programme that can take many forms and adapt to different curriculums. Here, the students have chosen to adapt three modules, but there are more, particularly concerning the societal aspects of life in the settlement on the exoplanet, and especially the return to Earth to apply the results of the thought experiment to real and concrete situations. In its pilot phase for the whole of 2024, IdeaSquare Planet will become a fully-fledged educational programme next year. The management of resources on which the students focused is a major issue for our present and future societies. By offering the opportunity to see passionate discussions about them sparkle in a science fiction imagination, the students allow their game to confront the players, as much as themselves, with the questions of tomorrow.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.811
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1890.048

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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