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Record W7027964179

Djokovic complains of weed smell at Montreal match

2015· other· en· W7027964179 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2015
Typeother
Languageen
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsnot available
Fundersnot available
KeywordsWeedSmokeSet (abstract data type)Taste
DOInot available

Abstract

fetched live from OpenAlex

If you're going to smoke marijuana...don't do it around the world's best tennis player. At a Rogers Cup match in Montreal over the weekend, Novak Djokovic complained to the umpire that he could smell marijuana coming from the stands...and claimed it was making him dizzy. Audio from ESPN...It obviously didn't make him THAT dizzy, because he cruised to a straight set win over France's Jeremy Chardy in the semifinals.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.889
Threshold uncertainty score0.614

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1110.021

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 head0.055
GPT teacher head0.324
Teacher spread0.269 · 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.

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
Published2015
Admission routes1
Has abstractyes

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