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Record W1899992016

Radish (Raphanus sativa L. cv. Cherry Bomb II) Growth, Net Carbon Exchange Rate, and Transpiration at Decreased Atmospheric Pressure and / or Oxygen

2012· article· en· W1899992016 on OpenAlexaff
Michael Stasiak, Cara Ann Wehkamp, Jamie Lawson, N.C. Yorio, Gary W. Stutte, Jeffrey Richards, Raymond M. Wheeler, Michael Dixon

Bibliographic record

VenueGravitational and Space Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTranspirationPartial pressureOxygenChemistryCarbon dioxideRaphanusHorticultureRespirationTotal pressureAnimal scienceAmbient pressureBotanyPhotosynthesisBiology
DOInot available

Abstract

fetched live from OpenAlex

To simplify engineering requirements for plant growth structures on the Moon or Mars, lower pressures are desirable to reduce mass and decrease atmospheric leakage. In order to establish the effect of reduced pressure and reduced oxygen on carbon assimilation, dark period respiration, transpiration and plant growth, radishes (Raphanus sativa L. cv. Cherry Bomb II) were grown at 98 (ambient pressure), 66 (2/3 atm), 33 (1/3 atm), and 10 (1/10 atm) kPa total pressures with oxygen partial pressures of 20, 14, 7, and 2 kPa for 21 days. All plants were grown in rockwool using recirculating nutrient film technique hydroponics. Analysis of growth showed no significant difference among the 98, 66, 33, and 10 kPa total pressure environments when the oxygen partial pressure was ≥ 7 kPa, but a significant reduction was observed when the oxygen partial pressure was dropped to 2 kPa, regardless of the total pressure. Net carbon exchange rate (NCER) and transpiration showed a similar pattern, with no significant effect with pressure treatments. Only the reduced oxygen partial pressure treatment of 2 kPa resulted in significant reductions in NCER and transpiration. Results indicate that pressure has little effect on radish productivity as long as oxygen levels are maintained at or above 7 kPa.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.042
GPT teacher head0.279
Teacher spread0.237 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2012
Admission routes1
Has abstractyes

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