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Record W4250149264 · doi:10.1017/s0714980800002981

CJG volume 24 issue 4 Cover and Back matter

2005· paratext· en· W4250149264 on OpenAlexafffund
Larry H. Thompson, Dolores Thompson, David W. Coon, Paulette C. Y. Tang, Pearl M. Mosher-Ashley, Joseph R. Sharkey, Ellen Taira, Hilary Einsohn, Ellen Csikai, Bert Hayslip, Brian Devries, Julie Hicks Patrick, Robert Kastenbaum, Robert W. Butler, Patricia Campione, Michael S. Caserta, Paul T. Costa, Stephen J. Cutler, Karen L. Fingerman, Peter Fry, Howard Giles, Jaber F. Gubrium, Robert O. Hansson, Gregory A. Hinrichsen, Jon Hendricks, Rob John, Michael B. Kleiman, Neal Krause, Robert J. Maiden, Jennifer A. Margrett, Sarah Matthews, William Mcauley, Susan H. McFadden, Morris A. Okun, Paul Panek, Rachel Pruchno, George W. Rebok, Kathryn Riley, Karen A. Roberto, K. Warner Schaie, Richard A. Settersten, Lisa Heather, Jan Servaty-Seib, Gregory Sinnott, Anne K. Smith

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of Toronto
FundersInstitute of AgingUniversity of CambridgeGovernment of Canada
KeywordsCover (algebra)Volume (thermodynamics)Action (physics)Content (measure theory)Computer scienceEngineeringMathematicsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

At the Press we combine ongoing experience with the latest in technological advances.The Press offers customers a full range of desktop publishing and printing services, including duplicating, typesetting, printing, binding, design and editing services, estimating, and production consultation.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.167
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.8330.740

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 head0.017
GPT teacher head0.189
Teacher spread0.172 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2005
Admission routes2
Has abstractyes

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