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Record W2888929226 · doi:10.20361/dr29366

Toca Lab: Plants by T. Boca

2018· article· en· W2888929226 on OpenAlexvenueaboutno aff
Katherine Schock

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2018
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Boca, Toca. Toca Lab: Plants. June 2017. Version 1.1.1. iTunes App Store, https://itunes.apple.com/app/apple-store/id1225994089?mt=8 Ages: 4-6Price: $2.99Available for Apple, Google Play, and Kindle Fire Toca Lab: Plants, from developer Toca Boca complements other apps in the Lab series, which aim to make science accessible through play. Toca Lab: Plants provides an open and unstructured environment to both nurture and experiment with plants. Upon opening the app, players enter a lab where a plant bobs happily in in the center, waiting to be played with; the plants are quite friendly and invite the player to interact. Five lab stations offer chances to experiment: a grow light, watering tank, nutrition station, cloning machine, and crossbreeding apparatus. In playing with these lab tools, the player can propagate plants, discover new plants, nurture others in pots, and keep track of them all in a botany chart. The plants, as characters in this app, are endearing. They respond with joy and exuberance to stimuli they like and with fear and shudders at stimuli they dislike. They even giggle and shake their leaves in response to touch. The lab itself is visually interesting and begs to be explored. Each station has machines to turn on, knobs to crank, faucets to open, or buttons to push. Since the play is wordless and largely without text (species are labelled with their Latin and common names at some points), the sound effects help to clarify what is happening and the materials in use, such as running water or electricity. The graphics are classic Toca Boca: beautiful bold colours, exaggerated blocky shapes, quirky plant characters, and uncluttered scenes. While all these elements – the app’s open play that supports experimentation and discovery, the beautiful visuals, and the endearing plants – make for a compelling play experience initially, the app is limited in extending play beyond these initial encounters. When compared with the imaginative possibilities in Toca Builders or Toca Blocks, for example, which allow users to create new spaces, scenes, structures, and worlds, Toca Lab: Plants feels limited. Players can only create so many new plants before the species begin to repeat themselves. Similarly, with the experiments, once all the plants have been moved through each experiment, the play is essentially mastered. Other than the plant chart (which is simply compiled as the player plays), there is no opportunity to construct something here, such as a garden or living structure with which to extend the world. Still, the app is beautiful and engaging, invites discovery and experimentation, and provides surprises and excitement as plants grow and change in response to the player’s actions. There is much fun to be had here in Toca Lab: Plants. Recommended: 3 out of 4 starsReviewer: Katherine Schock Katherine is a high school English teacher currently working on an MLIS at the University of Alberta. Her passion for children’s literature is kindled daily by her two small children and her much larger students.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.687
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6870.596

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 head0.012
GPT teacher head0.309
Teacher spread0.297 · 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 designQualitative
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
Published2018
Admission routes2
Has abstractyes

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