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2014· article· en· W4238643345 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSignificance · 2014
Typearticle
Languageen
FieldMathematics
TopicCensus and Population Estimation
Canadian institutionsnot available
Fundersnot available
KeywordsNOMINATELock (firearm)Reading (process)HistoryClassicsArt historyStatisticsPhilosophyMathematicsArchaeologyLinguistics

Abstract

fetched live from OpenAlex

Abstract Books reviewed in this issue. What is the best book you have read this year? We asked readers to nominate their favourites Math on Trial Leila Schneps and Coralie Colmez How Not to be Wrong Jordan Ellenberg Statistics: Unlocking the Power of Data Robin H. Lock, Patti Frazer Lock, Kari Lock Morgan, Eric F. Lock and Dennis F. Lock Past, Present, and Future of Statistical Science Xihong Lin, Christian Genest, David L. Banks, Geert Molenberghs, David W. Scott, and Jane-Ling Wang Statistics in Action: A Canadian Outlook Jerald F. Lawless Naked Statistics Charles Wheelan; W. W. Norton & Co. Modeling Count Data Joseph M. Hilbe

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.204

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 head0.065
GPT teacher head0.335
Teacher spread0.270 · 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