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Record W7040342193

The Migration

2019· book· en· W7040342193 on OpenAlexaboutno aff

Bibliographic record

VenueAnglia Ruskin Research Online (Anglia Ruskin University) · 2019
Typebook
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionTSG101PretextGestational periodCircumstantial evidenceHyporeflexia
DOInot available

Abstract

fetched live from OpenAlex

When I was younger I didn’t know a thing about death. I thought it meant stillness, a body gone limp. A marionette with its strings cut. Death was like a long vacation–a going away. Not this.
\n
\nStorms and flooding are worsening around the world, and a mysterious immune disorder has begun to afflict the young. Sophie Perella is about to begin her senior year of high school in Toronto when her little sister, Kira, is diagnosed. Their parents’ marriage falters under the strain, and Sophie’s mother takes the girls to Oxford, England, to live with their Aunt Irene. An Oxford University professor and historical epidemiologist obsessed with relics of the Black Death, Irene works with a Centre that specializes in treating people with the illness. She is a friend to Sophie, and offers a window into a strange and ancient history of human plague and recovery. Sophie just wants to understand what’s happening now; but as mortality rates climb, and reports emerge of bodily tremors in the deceased, it becomes clear there is nothing normal about this condition–and that the dead aren’t staying dead. When Kira succumbs, Sophie faces an unimaginable choice: let go of the sister she knows, or take action to embrace something terrifying and new.
\n Tender and chilling, unsettling and hopeful, The Migration is a story of a young woman’s dawning awareness of mortality and the power of the human heart to thrive in cataclysmic circumstances.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.003

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 head0.023
GPT teacher head0.255
Teacher spread0.232 · 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.

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
Published2019
Admission routes1
Has abstractyes

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