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Record W2528345476 · doi:10.20361/g2xk65

Harry Potter and the Half-Blood Prince by J.K. Rowling

2016· article· en· W2528345476 on OpenAlexvenueaboutno aff
Colemon BCR

Bibliographic record

VenueThe Deakin Review of Children s Literature · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHarry potterFavouriteMAGIC (telescope)ArtArt historyTheologyPhilosophyPhysics

Abstract

fetched live from OpenAlex

Rowling, J. K. Harry Potter and the Half-Blood Prince. Vancouver: Raincoast Books, 2005. Print.[Spoiler Alert!]I liked the part where Harry Potter used magic on Snape because it was cool and because Snape was trying to kill Harry Potter. I liked the part where Snape killed Dumbledor because Harry Potter saw it and had proof that it was Snape who was the half-blood prince. I didn’t like the part where Harry Potter was using an umbrella to spray the cabin because it was a boring waste of 2 pages of Harry Potter and Hagrid talking. I would recommend this book to family and friends and also to teachers.[Recommended: 3 out of 5 stars]Reviewer: ColemonHi I’m Colemon. I’m 11 years old. I like to read books and skateboard. My favourite trick is a 360 flip and my favourite book is Harry Potter or the BFG.

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)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0030.002
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.006

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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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
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
Published2016
Admission routes2
Has abstractyes

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