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Record W40098040 · doi:10.20361/g2rp6n

Mousetronaut by M. Kelly

2014· article· en· W40098040 on OpenAlexvenueaboutno aff
Trish Chatterley

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsnot available
Fundersnot available
KeywordsSpace ShuttleSpace (punctuation)AeronauticsAppealLift (data mining)Computer scienceHistoryLawEngineeringPolitical scienceAerospace engineeringOperating system

Abstract

fetched live from OpenAlex

Kelly, Mark. Mousetronaut. New York: Simon & Schuster, 2012.Several mice are training hard in the hope of being chosen to take part in a NASA space flight. Meteor the Mouse is much smaller than the others, but his hard work is recognized by the Shuttle Commander who chooses him as one of the six lucky mice to board the shuttle! Only Meteor adapts well to zero-gravity. He saves the mission when, because of his small size, he is able to rescue the key to the control panel when it gets stuck between two monitors.While kind of cute, especially when you learn the story is loosely based on a real mouse, I was left underwhelmed. It is a picture book, so the story is very short and more suited to the younger children in the recommended age range of 4-8. There’s no mention of why the mice were taken to space in the first place. While the story has a somewhat positive message in that sometimes the underdog can save the day, it wasn’t the fact that Meteor was a hard worker that led to his success but merely the fact that he was small.The illustrations by C.F. Payne vary in their appeal. The images of the space shuttle at lift-off and the astronauts floating in their spacesuits have an authentic feel, and the facial expressions of the mice in space are priceless. The human faces, however, are more like caricatures for an older audience with their sometimes oddly shaped faces and exaggerated noses. It was great to see a female among the astronauts, but the use of shading made her look as though she had as much five o’clock shadow as the men.The best part of the work is the afterword where the author, a retired astronaut, shares facts about the NASA program and life in space. Kids will learn some fun details, like that astronauts have to swallow their toothpaste! There is a list of recommended reading for further information, as well as a list of websites with videos or interactive games. This was the first installment of what might become a series of adventures (Mousetronaut Goes to Mars was released October 2013) so one hopes for more riveting plots in the further stories.Recommended with Reservations - 2 out of 4 starsReviewer: Trish ChatterleyTrish is a Public Services Librarian for the John W. Scott Health Sciences Library at the University of Alberta. In her free time she enjoys dancing, gardening, and reading books of all types.

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)0.000
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 score0.382
Threshold uncertainty score0.881

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3820.427

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 head0.003
GPT teacher head0.233
Teacher spread0.230 · 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
Published2014
Admission routes2
Has abstractyes

Explore more

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