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Record W7108644445 · doi:10.18712/nsd-nsd0673-v3

Omnibus Study No. 3 2002

2025· dataset· W7108644445 on OpenAlexaboutno aff

Bibliographic record

VenueNSD – Norsk senter for forskningsdata · 2025
Typedataset
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryQuarter (Canadian coin)NorwegianGovernment (linguistics)Official statisticsHealth statistics

Abstract

fetched live from OpenAlex

Statistics Norway's Omnibus Surveys are composed of questions about various themes on behalf of several employers. The surveys consist of a fixed set of background variables, as well as the questions that employers pay for. The questions that are determined by employers can almost be considered as fixed as well, since they are used each quarter. These questions concern smoking (on behalf of the Ministry of Health Care Services) and travel over the last three months (on behalf of the Section for Transport, Tourism and ICT at SSB). Other themes that were asked about in this quarter were:1. Smokinghabits Norwegian Directorate of Health2. Traveling over the last 3 months Statistics Norway 3. Live-in statistics Statistics Norway 4. Expenditure in relation to traveling Ministry of Trade and Industry5. Attitudes toward immigration/immigrants Ministry of Local Government and Regional DevelopmentThe Omnibus Survey in August/September (Omnibus nr. 3) 2002 was the third of four Omnibus Surveys in 2002.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.116
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.012
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1160.086

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 head0.024
GPT teacher head0.322
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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