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Record W4251917909 · doi:10.1017/s0714980800017098

CJG volume 23 issue 4 Cover and Back matter

2004· paratext· en· W4251917909 on OpenAlexafffund
W Canadian, 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, William Mcauley, Susan H. McFadden, Sarah Matthews, Morris A. Okun, Paul Panek, Rachel Pruchno, Kathryn Riley, Karen A. Roberto, K. Warner Schaie, Heather L. Servaty, Jan D. Sinnott, Gregory C. Smith, Anne M. Wyatt-Brown, Caoinq Vnvlqmmil

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2004
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of TorontoECW Press (Canada)Canadian Nurses Association
FundersGovernment of CanadaAmerican Psychological Association
KeywordsCover (algebra)Volume (thermodynamics)Content (measure theory)Action (physics)Computer scienceMathematicsEngineeringPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

AIMS & SCOPEUnder what conditions does "development" end?Under what conditions does "aging" begin?Can these conditions themselves be modified by intervention at the psychological, social, or biological levels?To what extent are patterns of development and aging attributable to biological factors?To psychological factors?How can the social and behavioral sciences contribute to the actualization of human potential throughout the entire life span?What are the implications of gerontological research for our understanding of the total development of human organism?These are some of the broad questions with whichThe International Journal of Aging & Human Development is concerned.Emphasis is upon psychological and social studies of aging and the aged.However, this peerrefereed journal also publishes research that introduces observations from other fields that illuminate the "human" side of gerontology, or utilizes gerontological observations to illuminate problems in other fields.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.649
Threshold uncertainty score0.500

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.6490.523

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 head0.016
GPT teacher head0.188
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; a candidate call from one source (direct Gemma or distilled Codex), 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
Published2004
Admission routes2
Has abstractyes

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