MétaCan
Menu
Back to cohort
Record W7055559099

Computer predicts Norway to strike gold at 2018 winter olympics

2017· other· en· W7055559099 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2017
Typeother
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEntertainmentTable (database)Gold coastEntertainment industry
DOInot available

Abstract

fetched live from OpenAlex

Using a computer program, the U.S.-based sports and entertainment provider Gracenote predicts Norway will be at the top of the table with 40 medals - a Winter Olympic record for overall medals. It would surpass the 37 the United States won at the 2010 Vancouver Games. Norway is looking at a record performance in the upcoming winter Olympics in South Korea......that's if you believe the computer at one sports and entertainment company.The company is called Gracenote and it predicts Norway could win 40 medals.That's three more than the overall record of 37 that the United States won at the 2010 Vancouver Games.The computer also forecasts Germany'll win 34 medals, and the U.S. 32.It's more of the same when you're just looking at gold medals......Gracenote predicts 15 gold for Norway and 13 for Germany while the U.S. and France will tie at 10.

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)0.000
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.008

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternet Archive (Internet Archive)Same topicParticle accelerators and beam dynamicsFrench-language works237,207