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Record W7059805757

UNLV 101

2012· article· nl· W7059805757 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Scholarship - UNLV (University of Nevada Reno) · 2012
Typearticle
Languagenl
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Quarter (Canadian coin)Avascular necrosis
DOInot available

Abstract

fetched live from OpenAlex

Quick, what's the medical term for avascular necrosis of the lunate?Give up?A group of UNLV athletic training students didn't, and their correct answer won the National Athletic Trainers' Association quiz bowl championship.(The answer is Kienbock disease.)The UNLV team -Cody Bremner, Christine Samson, and Shun Jinnouchi -bested 10 schools in a Jeopardy-style competition."We didn't expect to win by such a large margin," says Bremner about the 28,303 points they amassed.The University of Florida was a distant second with 11,011. 1 National Champions Powerful Idea, Powerful Award 2 UNLV's student chapter of the American Marketing Association ranks in the top 2 percent of student AMA chapters worldwide after winning the Silver Chapter Award at the annual American Marketing Association International Collegiate Conference.UNLV students have also won the AMA website competition in recent years.In addition, the group took third place in the national Nintendo Case Competition -the chapter's fifth consecutive trip to the finals.3 Top of Their GameEngineering students Wali Zaidi, Sammy Zaidi, and Christopher Belcher had an idea about how to help people in developing nations: bring affordable power to rural areas to improve education, health care, and economic development.They won the United Nations Foundation Technology Challenge for their design of an affordable solar-tracking power system for small-scale appliances like a household lights, computers, or refrigerators.

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 score0.279
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7210.506

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 head0.018
GPT teacher head0.196
Teacher spread0.178 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

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