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Measurement Burst Design

2015· other· en· W2782353864 on OpenAlexaff
Robert S. Stawski, Stuart MacDonald, Martin J. Sliwinski

Bibliographic record

VenueThe Encyclopedia of Adulthood and Aging · 2015
Typeother
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Victoria
FundersNational Institutes of Natural SciencesNational Institute on AgingNational Institutes of Health
KeywordsTerm (time)Computer sciencePhysics

Abstract

fetched live from OpenAlex

The measurement burst design is a design that incorporates bursts of intensive repeated assessment within a relatively short period of time (e.g., days, weeks) that are repeated longitudinally, over more widely spaced temporal intervals (e.g., annually). This design lends itself to the study of short‐term variability, long‐term change, and individual differences therein. Further, the measurement burst design facilitates the study of dynamic processes that transpire over different temporal scales and how these processes influence one another. This entry describes the measurement burst design, giving examples of its application in adult development and aging research and of the virtues and challenges involved with its implementation.

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 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 score0.029
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.056
GPT teacher head0.327
Teacher spread0.271 · 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.

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

Citations49
Published2015
Admission routes1
Has abstractyes

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