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Record W7066300175

[FSCR-TV] Charlotte Hornets vs Philadelphia 76ers:Live Stream (NBA Basketball Online 2019)

2019· other· en· W7066300175 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2019
Typeother
Languageen
FieldComputer Science
TopicMachine Learning and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsVictoryCONTESTShot (pellet)BasketballQuarter (Canadian coin)Line (geometry)
DOInot available

Abstract

fetched live from OpenAlex

The Philadelphia 76ers have been in great shape as they’ve won nine of their last 13 games and they will be gunning for a fifth straight victory after sneaking past the Bucks in a 130-125 road win on Sunday. Joel Embiid dominated the game with 40 points, 15 rebounds and six assists, Jimmy Butler added 27 points while JJ Redick chipped in with 19 points on seven of 10 shooting. ==================== Watch LIVE:: https://247itv.info/nba-allaccess Watch LIVE:: https://247itv.info/nba-allaccess ==================== As a team, the 76ers shot 47 percent from the field and 15 of 32 from the 3-point line as they poured on 62 points in the first half to lead by nine points going into halftime, but they had to keep the offense going in the fourth quarter where the Bucks rallied with 43 points. With the impressive win, Philadelphia improved to 45-25 overall and 17-16 on the road. Meanwhile, the Charlotte Hornets have been in a rut as they’ve lost eight of their last 11 games and they will hoping to bounce back after getting blown out by the Heat in a 93-75 road loss on Sunday. Jeremy Lamb led the team in scoring with 21 points off the bench, Frank Kaminsky added 13 points while Nicolas Batum chipped in with 12 points but no other player scored more than 10 points. As a team, the Hornets shot a season-low 31 percent from the field and seven of 36 from the 3-point line as they hung with the Heat in a close contest until the fourth quarter where the Heat outscored them by 32-15 to run away with it late. With the loss, Charlotte fell to 31-38 overall and 10-24 on the road. Looking at the betting trends, the 76ers are 1-5 ATS in their last six games against a team with a losing record and 5-2 ATS in their last seven games after allowing 100 points or more in their previous game. The Hornets are 4-1-1 ATS in their last six games following a loss of more than 10 points, 18-38-4 ATS in their last 60 games against a team with a winning record and 1-6 ATS in their last seven games overall. Head to head, the road team is 4-0 ATS in the last four meetings, the 76ers are 4-0 ATS in the last four meetings in Charlotte and the 76ers are 7-2 ATS in the last nine meetings overall. The Hornets opened as minor favorites in this one which was surprising, but the early money is going towards the 76ers who have been in great form lately. The 76ers are also 4-0 ATS in the last four meetings in Charlotte and 7-2 ATS in the last nine meetings overall, so I’m keeping it simply and taking the 76ers to continue their surge towards the playoffs with another win and cover in this one.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.330
Threshold uncertainty score0.471

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6700.356

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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; the direct Gemma label and the distilled Codex classifier 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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