MétaCan
Menu
Back to cohort

Wheeler Raymond Agriculture for Space: People and Countries Paving the Way

2017· article· ru· W2773755293 on OpenAlex
Wheeler Raymond

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueИсследования космоса · 2017
Typearticle
Languageru
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)AgricultureGeographySociologyBusinessArchitectural engineeringComputer scienceEngineeringArchaeology

Abstract

fetched live from OpenAlex

Agricultural systems for space have been discussed since the works of Tsiolkovsky in the early 20th century. Central to the concept is the use of photosynthetic organisms and light to generate oxygen and food. Research in the area started in 1950s and 60s through the works of Jack Myers and others, who studied algae for O2 production and CO2 removal for the US Air Force and NASA. Studies on algal production and controlled environment agriculture were also carried out by Russian researchers in Krasnoyarsk, beginning in 1960s. NASA initiated its CELSS Program ca. 1980 with testing focused on controlled environment production of some plants. Related tests with humans and crops were conducted at NASA’s Johnson Space Center in the 1990s. The European Space Agency MELiSSA Project began in the late 1980s and pursued ecological approaches for providing gas, water and materials recycling for space life support, and later expanded to include plant testing.As a result of these and other (Japan, Canada, China) studies for space agriculture novel technologies and findings have been produced. The theme of agriculture for space has contributed to, and benefited from terrestrial, controlled environment agriculture and will continue doing so into the future.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.186
Teacher spread0.182 · 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