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Record W4400022447 · doi:10.7302/23418

Motion Sickness

2024· article· en· W4400022447 on OpenAlexaboutno aff
Alex McCullough

Bibliographic record

VenueDeep Blue (University of Michigan) · 2024
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMotion sicknessMedicine

Abstract

fetched live from OpenAlex

In this collection of stories from Toledo-based writer Alex McCullough, young adulthood and all its various joys and sorrows are rendered with equal measures humor and poignancy. In one story, a young woman and her sister confront their father at a dinner party celebrating his engagement to his second wife. In another, a sheltered boy and his charismatic new neighbor conspire to cross the Canadian border, with disastrous aftermath. In another, a young woman, failing out of her prestigious university, struggles through a torturous Thanksgiving dinner with her extended family. In another, a dysregulated young man yearns for metamorphosis as the anniversary of a past trauma looms in the near future. The narrators of these seven stories are all at a crossroads. They face unrequited love, disillusionment, self-destructive habits, crippling nostalgia, conflicts of identity and sense of place, familial strife, and the perennial quandary: how do we possibly navigate these delicate years? How do we ever make it out the other side?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.202
Teacher spread0.192 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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