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Record W7093481221

Josephine Burnett

2020· article· W7093481221 on OpenAlexaboutno aff

Bibliographic record

VenueScholarly Commons (Embry–Riddle Aeronautical University) · 2020
Typearticle
Language
FieldEngineering
TopicSpace Exploration and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPayload (computing)International Space StationSpace ShuttleTest (biology)LaunchedSpace (punctuation)Space researchSpace technologyNASA Chief Scientist
DOInot available

Abstract

fetched live from OpenAlex

Josephine Burnett is the director of Exploration Research and Technology Programs at NASA's John F. Kennedy Space Center in Florida. She is responsible for strategic leadership and program and project management for Kennedy support to the Exploration mission, which includes Space Life and Physical Sciences (SLPS), International Space Station (ISS), Advanced Exploration Systems (AES), and Space Technology (ST) Programs.\nBurnett began her career with NASA in 1987 as an aerospace/mechanical engineer integrating experiments onto Spacelab racks and pallets. In 1991, she became an experiment project engineer and led a team of engineers in the test and checkout of the United States Microgravity Laboratory–1 Spacelab Module. Burnett moved to an operations position in 1993 as a payload test director. In this position, she was responsible for overseeing shuttle payload testing for assigned payloads, including payload support for launch countdown.\nIn 1995, Burnett served as the center director management Intern and performed in this capacity until 1996 when she joined the Space Station Hardware Integration Office. For three years, she supported the test and checkout of the Canadian Space Station Remote Manipulator System (SSRMS) in Brampton, Ontario, and the Canadian portion of the Multi Element Integrated Test, after which time she was selected to lead the Element 6A Office as the acting chief.\nIn 2000, Burnett joined the ISS/Payload Processing Directorate as the chief of the Future Missions and International Partner Division. In this position, she led the office responsible for the advanced planning of ISS international elements, shuttle payloads, and concepts for improved ways to test payloads in the future. In 2003, she returned to the directorate as deputy for Program Management for the ISS and Payload Processing Directorate and the Kennedy Space Center. In this capacity, she supported the director in the development of organizational roles and responsibilities, as well the development of long-range organizational direction for Kennedy and ISS Program needs.\nBurnett was selected as a member of the Senior Executive Services Career Development Program (SESCDP) class of 2004 and completed the program in March 2006. She returned to Kennedy as the chief of the Systems Engineering and Integration Division for Kennedy’s Josephine Burnett Credits: NASA Design Engineering Directorate. In this capacity, she led a team of highly experienced systems engineers in support of the Constellation Ground Operations Project.\nBurnett then became the deputy director of the Space Transportation Planning office, providing strategic guidance and leadership for the program management and systems engineering and integration of the Constellation Block 1 Orion/Ares configuration to low-Earth orbit.\nMost recently, she was the director of the ISS Ground Processing and Research Project Office responsible for all ground processing of space station elements from around the world. These elements are operating in orbit and supporting the largest, most complex space station in human history.\nBurnett graduated from the University of Florida in 1987 with a B.S. in aerospace engineering and, in 1991, earned a Master of Science from the Florida Institute of Technology in space system operations. She is a native of Florida and lives in Merritt Island with her family.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.004

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 head0.036
GPT teacher head0.196
Teacher spread0.160 · 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
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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