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Record W6905133764 · doi:10.15139/s3/k03yhd

Toronto Couples Study, 2017

2019· dataset· en· W6905133764 on OpenAlexaffabout

Bibliographic record

VenueUNC Dataverse · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSession (web analytics)InterviewOnline forumData collectionWork (physics)Protocol (science)

Abstract

fetched live from OpenAlex

This dataset was collected at the University of Toronto between 2015-2017. Romantic couples from the community participated in a four-part study. To be eligible, couples were required to be in a relationship for at least 3 years. A total of 111 couples completed the study. The four parts of the study included (1) completing a background questionnaire; (2) participating in a lab session in which they were connected to physiological equipment and held three conversations, alternating as speakers and listeners, on the topics of (a) a time when they felt distressed, (b) something they would like their partner to change and (c) something about their partner they feel grateful for; and completed questionnaires about these conversations; (3) completing a 14-day daily experience (“diary”) study; and (4) completing a follow-up questionnaire the day after the diary. In addition, a subset of these participants was rated by their work supervisors. Data have been collected for this study in full. The protocol reference number for ethics approval of this study is 31063.

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 categoriesMeta-epidemiology (narrow), Insufficient 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.671
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0490.721

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 head0.046
GPT teacher head0.322
Teacher spread0.275 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes2
Has abstractyes

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