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Record W7068922120

Bob Richards

2016· article· en· W7068922120 on OpenAlexaboutno aff

Bibliographic record

VenueScholarly Commons (Embry–Riddle Aeronautical University) · 2016
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsSpace ScienceAerospaceSpace (punctuation)Mars Exploration ProgramSpace ShuttleSpace researchMartianSpaceflightHuman spaceflight
DOInot available

Abstract

fetched live from OpenAlex

Bob Richards, Co-founder, President & CEO, Moon Express Dr. Robert (Bob) Richards is a space entrepreneur and futurist. He is a Co-Founder of the International Space University, Singularity University, SEDS, the Space Generation Foundation and Moon Express, Inc. a lunar resources company competing in the $30M Google Lunar X PRIZE, where he currently serves as President and CEO. Bob chairs the space commerce committee of the Commercial Spaceflight Federation and is a member of the International Institute of Space Law. As Director of the Optech Space Division from 2002-2009, Bob led the company's technology into orbit in 2004 and to the surface of Mars in 2007 aboard the NASA Phoenix Lander, making the first discovery of falling Martian snow. Bob studied aerospace and industrial engineering at Ryerson University; physics and astronomy at the University of Toronto; and space science at Cornell University where he became special assistant to Carl Sagan. In 2005 Bob received a Doctorate of Space Achievement (honoris causa) from the International Space University for “distinguished accomplishments in support of humanity’s exploration and use of space.”

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)0.005
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 score0.701
Threshold uncertainty score1.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 integrity0.0020.004
Insufficient payload (model declined to judge)0.2990.206

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 head0.026
GPT teacher head0.231
Teacher spread0.205 · 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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