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Record W4388981307 · doi:10.1515/9781773854694

Flicker

2023· book· en· W4388981307 on OpenAlexaboutno aff
Lori Hahnel

Bibliographic record

VenueUniversity of Calgary Press eBooks · 2023
Typebook
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsnot available
Fundersnot available
KeywordsFlickerComputer scienceComputer graphics (images)

Abstract

fetched live from OpenAlex

Cass Reisender doesn’t enjoy her psychic abilities. They appeared after her parents were killed in a tragic accident and led her to Madame Freyja, a travelling fortune teller and all-round terrible person. Swearing to leave both her psychic sensitivity and Madame Freyja behind, Cass starts again in Calgary, Alberta, a city with nothing supernatural about it at all. Then Cass touches a strange antique device and her new life is blown apart. Transported to West Orange, New Jersey, in the year 1900, Cass meets the dashing Erik Thorvaldsen in Thomas Edison’s – that Thomas Edison’s – laboratory. As she and Erik grow closer, Cass finally accepts herself as she finds love in a life lived across centuries. Yet Madame Freyja lurks in the shadows, hungry for the power of the time travel device. When Madame Freyja strikes, Cass must face both her fears and her past or lose her connection to Erik forever. Flicker is a playful, fast-paced romp through the golden age of invention, mythology, and the supernatural. This is a novel for everyone who believes in the power of scientific curiosity and the strength of the human heart.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.364
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3640.169

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 head0.018
GPT teacher head0.177
Teacher spread0.159 · 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
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
Published2023
Admission routes1
Has abstractyes

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