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Record W3146408711 · doi:10.20361/g20k75

Smile by R. Telgemeier - 2nd review

2016· article· en· W3146408711 on OpenAlexvenueno aff
Shauna BCR

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsFront pageFront (military)PsychologyVisual artsArtMedia studiesSociologyEngineering

Abstract

fetched live from OpenAlex

Telgemeier, Raina. Smile. New York: Scholastic, 2010. Print I picked the book Smile to review because it tells you about the author's childhood. Going to the dentist, getting braces, going for gum surgery, severely injuring her two front teeth, and getting fake ones, while that's going on, she was in a major earthquake. After getting braces her friends were making fun of her and when she finally left middle school and goes off to high school she finds new friends that are kind to her. And then when she got her braces off they did not make fun of her. That's how she knew she found her true friends. I give this 4 out of 5. I recommend this book to anybody that likes graphic novels.Recommended: 4 out of 4 stars Reviewer: ShaunaMy name is Shauna and I like to read graphic novels.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.049
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0490.061

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 head0.008
GPT teacher head0.225
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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