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Record W7050202010

Not Very Much

2015· article· en· W7050202010 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons @ Butler University (Butler University) · 2015
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsnot available
Fundersnot available
KeywordsKindnessQuarter (Canadian coin)EveningPost officeWork (physics)ThursdayCoronation
DOInot available

Abstract

fetched live from OpenAlex

MAGGIE Malone tucked number in t 0 her shabby purse and goodby to Dominic. Each evening he gave her a ride home from the department store where she worked as a seamstress in the alterations room. Tonight, Dominic had sold her a quarter chance in a pool sponsored by the Italian churches of the city; he had sold the chances all along his vegetable route. At first Maggie argued that she just couldn't afford it. Why, she was behind on her rent as it was, and if it weren't for the kindness of old Mrs. Ruben, she'd be without a room now. It took a long time to pay doctor bills on her salary, and when a body was old they stayed sick for such a long time that the bills came high. But Dominic said it was all for the Church, and, after all, wouldn't the good Lord and all the saints see to it that she won?

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)0.002
metaresearch head score (Gemma)0.013
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 score0.231
Threshold uncertainty score0.772

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0120.009
Open science0.0020.008
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.2310.175

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 head0.173
Teacher spread0.150 · 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
Published2015
Admission routes1
Has abstractyes

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