MétaCan
Menu
Back to cohort
Record W7134545311

Arthur Christmas

2017· article· W7134545311 on OpenAlexaboutno aff
Amanda Durrant

Bibliographic record

VenueScholarsArchive (Brigham Young University) · 2017
Typearticle
Language
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsShot (pellet)Set (abstract data type)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

It's Christmas eve in the North Pole as the current Santa is preparing for what is thought to be his 70th and final mission of delivering presents. He doesn't use just an ordinary sleigh though, but a highly advanced spaceship called the S-1 that is managed by Santa's eldest son Steve. In the hustle and bustle of packing the sleigh, a present falls off the conveyor belt and is left behind. Santa's youngest son Arthur is on a mission to get the present delivered in time for Christmas morning, but Arthur is only responsible for the mail as he often messes things up. With the help of Bryony the elf and Grandsanta, Arthur loads the present onto the old model reindeer pulled sleigh. They set off, but encounter countless problems along the way and Arthur learns that Grandsanta is not there to help deliver the present, but for his own motives. Each of the men in Arthur's family find out that Arthur has a true heart of gold and deserves to be the next Santa as he successfully gets the forgotten present delivered and the joy of being Santa shows on his face.

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)0.005
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 score0.096
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0110.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0960.023

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 head0.017
GPT teacher head0.219
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueScholarsArchive (Brigham Young University)Same topicThemes in Literature AnalysisFrench-language works237,207