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Record W4401023189 · doi:10.1039/d4sm00712c

Engineering bacterial biomanufacturing: characterization and manipulation of <i>Sphingomonas</i> sp. LM7 extracellular polymers

2024· article· en· W4401023189 on OpenAlexfundno aff
Ellen van Wijngaarden, Alexandra G. Goetsch, Ilana Brito, David M. Hershey, Meredith N. Silberstein

Bibliographic record

VenueSoft Matter · 2024
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersCommon FundDivision of Materials ResearchNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Nanotechnology Coordinating OfficeArnold and Mabel Beckman FoundationNational Institutes of HealthNational Science Foundation
KeywordsBiomanufacturingCharacterization (materials science)ExtracellularChemistrySphingomonasPolymerNanotechnologyMicrobiologyChemical engineeringBacteriaMaterials scienceBiologyBiochemistryPseudomonasBiotechnologyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

sp. LM7; (2) demonstrates that these properties can be manipulated to suit specific applications; and (3) presents two alternative methods of processing to shorten purification time by more than 50% while maintaining comparable material properties.

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)0.000
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 score0.348
Threshold uncertainty score0.837

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 integrity0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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