MétaCan
Menu
Back to cohort
Record W2514994296 · doi:10.1007/s11120-016-0301-7

Interactive effects of nitrogen and light on growth rates and RUBISCO content of small and large centric diatoms

2016· article· en· W2514994296 on OpenAlexafffund
Gang Li, Douglas A. Campbell

Bibliographic record

VenuePhotosynthesis Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsMount Allison University
FundersNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Guangdong ProvinceCanada Foundation for InnovationNational Natural Science Foundation of ChinaCanada Research ChairsNew Brunswick Innovation Foundation
KeywordsRuBisCONitrogenPlant physiologyBotanyChemistryPhotosynthesisBiology

Abstract

fetched live from OpenAlex

Among marine phytoplankton groups, diatoms span the widest range of cell size, with resulting effects upon their nitrogen uptake, photosynthesis and growth responses to light. We grew two strains of marine centric diatoms differing by ~4 orders of magnitude in cell biovolume in high (enriched artificial seawater with ~500 µmol L−1 µmol L−1 NO3 −) and lower-nitrogen (enriched artificial seawater with <10 µmol L−1 NO3 −) media, across a range of growth light levels. Nitrogen and total protein per cell decreased with increasing growth light in both species when grown under the lower-nitrogen media. Cells growing under lower-nitrogen media increased their cellular allocation to RUBISCO and their rate of electron transport away from PSII, for the smaller diatom under low growth light and for the larger diatom across the range of growth lights. The smaller coastal diatom Thalassiosira pseudonana is able to exploit high nitrogen in growth media by up-regulating growth rate, but the same high-nitrogen growth media inhibits growth of the larger diatom species.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.026
GPT teacher head0.250
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations29
Published2016
Admission routes2
Has abstractyes

Explore more

Same venuePhotosynthesis ResearchSame topicMarine and coastal ecosystemsFrench-language works237,207