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Record W7048260153

John Isner vs Felix Auger-Aliassime Live Free

2019· other· en· W7048260153 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2019
Typeother
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsnot available
Fundersnot available
KeywordsChampionMiamiTournamentLeagueSet (abstract data type)
DOInot available

Abstract

fetched live from OpenAlex

Defending Champion John Isner takes on the fast-rising Canadian youngster Felix Watch Live NOW ► https://bit.ly/2KzLGxE GO LIVE🔴► https://bit.ly/2KzLGxE Watch Live NOW ► https://bit.ly/2KzLGxE Auger-Aliassime in the first semi-final of the 2019 Miami Open. Before the tournament, big John was not in the best of form this season, but he seems to have suddenly found his mojo back at Miami and looks very much like the defending champion that he is. Predictably, it has been his big serve that has played a major role in his progress so far. He has won all his matches in straight sets and seven of those eight sets have gone to tie-breaks, and he has won them all. Whether it is players with a lesser pedigree such as Lorenzo Sonego or the ones capable of much better tennis such as Kyle Edmund or Bautista Agut, his go-to method has been to ensure that he wins all his service games, and take the set to a tie-break, where his bigger serve gives him the advantage. He has been broken only twice in the tournament so far and has broken his opponents’ serve three times. In his quarterfinal match against Roberto Bautista Agut which he won in two tie-breaks, he kept 85 percent of his first serves in, winning 77 percent of those and won 58 percent of his second serves. His semi-final opponent, Auger-Aliassime has a contrasting game style. He does not possess the kind of big serve that Isner has, but his return game is markedly better than the American’s. As a result, in the five matches he has played so far in the tournament, we have seen lot many breaks of serve, unlike the matches involving Isner. The Canadian’s serve has been broken nine times in the tournament, but he has broken his opponents’ serve a whopping nineteen times as well. After two three-set matches in the first two rounds, he has won his last three matches in straight sets against players of the caliber of Borna Coric and Nikoloz Basilashvili. He has played two tie-breaks so far and has won them both. His match with Isner is expected to have at least one tie-break, if not more. And if that comes to pass, he will not only need to serve better but should also try to find a way to break Isner’s serve.

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)0.002
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 score0.353
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3530.109

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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
Published2019
Admission routes1
Has abstractyes

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