MétaCan
Menu
Back to cohort
Record W6925190723 · doi:10.17026/dans-xsm-ph59

Beleving van monumenten 1981

2013· dataset· en· W6925190723 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDANS Data Station SSH · 2013
Typedataset
Languageen
FieldComputer Science
TopicIntuitionistic Fuzzy Systems Applications
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Reading (process)BalletLeisure timeTable (database)

Abstract

fetched live from OpenAlex

<p>Information-processing and status acquiring determinants of cultural activities, especially visiting monuments. Visits to inner-city / finding one's way in inner-city and outskirts / recognition and appreciation of photo's of inner-city / visits to other cities, villages and old buildings / knowledge of history of Utrecht / modern developments in inner-city / protection and preservation of inner-city and number of areas outside inner-city and own quarter / leisure activities: reading/ museums and exhibitions/ concerts, theatre, opera, ballet and cabaret / parents: theatre, classical music, museums, old buildings, villages, cities, importance of reading books / important things in life. Background variables: basic characteristics/ residence/ housing situation/ household characteristics/ occupation/employment/ income/capital assets/ education/ readership, mass media, and 'cultural' exposure</p>

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.

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.314
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0050.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.005

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 head0.296
Teacher spread0.250 · 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