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Record W2142827876 · doi:10.1071/pp01184

The diversity of inorganic carbon acquisition mechanisms in eukaryotic microalgae

2002· article· en· W2142827876 on OpenAlexafffund
Brian Colman, I. Emma Huertas, Shabana Bhatti, Jeffrey S. Dason

Bibliographic record

VenueAustralian Journal of Plant Physiology · 2002
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHaptophyteBiologyTotal inorganic carbonAlgaeIsochrysis galbanaBotanyDiatomEcophysiologyCarbonic anhydraseAquatic plantRuBisCOMixotrophEcologyPhytoplanktonPhotosynthesisNutrientCarbon dioxideBiochemistryHeterotrophBacteria

Abstract

fetched live from OpenAlex

Eukaryotic microalgae have developed CO2concentrating mechanisms to maximise the concentration of CO2 at the active site of Rubisco in response to the low CO2 concentrations in the external aquatic medium. In these organisms, the modes of inorganic carbon (Ci) uptake are diverse, ranging from diffusive CO2 uptake to the active transport of HCO3-and CO2 and many have an external carbonic anhydrase to facilitate HCO3- use. There is unequivocal evidence for the mechanisms of Ci uptake in only about 25 species of microalgae of the chlorophyte, haptophyte, rhodophyte, diatom, and eustigmatophyte groups. Most of these species take up both CO2 and HCO3-, but the rates of uptake of each of these substrates varies with the algal species. A few species take up only one of the two forms of Ci, an adaptation that is not necessarily correlated with their ecological distribution. Evidence is presented for the active uptake of HCO3- and CO2 in two marine haptophytes, Isochrysis galbana Parke and Dicrateria inornata Parke, and for active transport of CO2 but lack of HCO3- uptake in two marine dinoflagellates, Amphidinium carterae Hulburt and Heterocapsa oceanica Stein.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.020
GPT teacher head0.208
Teacher spread0.188 · 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

Citations190
Published2002
Admission routes2
Has abstractyes

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