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Record W7095743788

ORIGINAL ARTICLE Fed-batch production of M

2016· article· en· W7095743788 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Oleic acidBioreactorScale (ratio)Composition (language)
DOInot available

Abstract

fetched live from OpenAlex

bt rat, 7 g tid Marchessault et al. 1990). Most bioreactor scale produc-tion of MCL-PHAs have used structurally related MCL this cultivation technique is not used commercially. In order to be of commercial interest, this novel approach to Jiang et al. AMB Express 2013, 3:50 http://www.amb-express.com/content/3/1/50growth rate and the β-oxidation inhibitor concentration in1Chemical Engineering, Queen's University, Kingston, ON K7L 3N6, Canada Full list of author information is available at the end of the articlecarbon substrates, such as octane (Hazenberg and Witholt 1997), nonanoic acid (Sun et al. 2007), and oleic acid (Lee et al. 2000). Although Liu et al. (2011) and Chung et al. (2011) effectively showed MCL homopolymer production MCL-PHA production must be shown to be applicable to fed-batch culture. The objective of this study was to develop a metho-dology for controlling the monomeric composition of MCL-PHA in efficient fed-batch fermentations. Specific-ally, the production of PHN copolymers with different HN content was investigated by controlling the specific * Correspondence:

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0050.001

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 head0.133
GPT teacher head0.488
Teacher spread0.355 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2016
Admission routes1
Has abstractyes

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