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Record W2937681215 · doi:10.1002/bit.26974

Direct capture and conversion of CO<sub>2</sub> from air by growing a cyanobacterial consortium at pH up to 11.2

2019· article· en· W2937681215 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiotechnology and Bioengineering · 2019
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsUniversity of Calgary
FundersCalgary Institute for the Humanities, University of CalgaryGovernment of AlbertaNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesCanada Foundation for InnovationCanada First Research Excellence Fund
KeywordsCyanobacteriaEnvironmental chemistryEnvironmental scienceChemistryBiologyBacteria

Abstract

fetched live from OpenAlex

Abstract Bioenergy with carbon capture and storage (BECCS) is recognized as a potential negative emission technology, needed to keep global warming within safe limits. With current technologies, large‐scale implementation of BECCS would compromise food production. Bioenergy derived from phototrophic microorganisms, with direct capture of CO 2 from air, could overcome this challenge and become a sustainable way to realize BECCS. Here we present an alkaline capture and conversion system that combines high atmospheric CO 2 transfer rates with high and robust phototrophic biomass productivity (15.2 ± 1.0 g/m 2 /d). The system is based on a cyanobacterial consortium, that grows at high alkalinity (0.5 mol/L) and a pH swing between 10.4 and 11.2 during growth and harvest cycles.

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 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 score0.015
Threshold uncertainty score0.642

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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