MétaCan
Menu
Back to cohort
Record W7068378832

The Lies We Tell

2020· dissertation· en· W7068378832 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2020
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeConsciousnessPower (physics)Accident (philosophy)Meditation
DOInot available

Abstract

fetched live from OpenAlex

The Lies We Tell is a semi-autobiographical novel about a gay man who falls into a coma, written by a gay man who has never been in a coma. The text explores topics including inter- generational relationships, online hookup culture in the mid-2000s, twins, and the nature of memory. The novel follows two protagonists, Dale and Luis, a couple of ten years living in Toronto who are on the brink of a breakup. Following a disastrous dinner party, Luis and Dale drive home (drunk) and get in a car accident (thanks to a deer), and thus begins Luis’s coma, during which he vividly relives — and reflects upon — his final year of high school. The novel is told through present- and past-tense narration in the third-person from both Dale and Luis’s perspectives. Inspired in part by other novels about characters in comas, the text uses multiple levels of dreamlike consciousness in an attempt to breathe new life into a tired literary trope. The characters' narrative arcs explore an array of themes, including a meditation on the lure of middle-class stability for gay men, how sexual abuse is internalized, and the terrifying power of self-deception.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.437

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 science0.0010.000
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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)Same topicMachine Learning in BioinformaticsFrench-language works237,207