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Record W3196854727 · doi:10.1016/j.isci.2021.103049

Pushing the methodological envelope in understanding the photo/electrosynthetic materials-microorganism interface

2021· review· en· W3196854727 on OpenAlexaff
Kiran Kuruvinashetti, Nikolay Kornienko

Bibliographic record

VenueiScience · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversité de Montréal
FundersAmerican Chemical Society
KeywordsInterface (matter)NanotechnologyEnvelope (radar)MicroorganismAstrobiologyChemistryEngineering physicsMaterials scienceComputer scienceBiologyEngineeringTelecommunicationsBiochemistry

Abstract

fetched live from OpenAlex

Biohybrid photo/electrosynthetic systems synergize microbial metabolic pathways and inorganic materials to generate the fuels and chemicals to power our society. They aim to combine the strengths of product selectivity from biological cells and efficient charge generation and light absorption of inorganic materials. However crucial mechanistic questions still remain. In this review we address significant knowledge gaps that must be closed and recent efforts to do so to push biohybrid systems closer to applicability. In particular, we focus on noteworthy advances that have recently been made in applying state-of-the-art analytical spectroscopic, electrochemical, and microelectronic techniques to help pinpoint key complexities of the microbe-materials interface. We discuss the basic function of these techniques, how they have been translated over to study biohybrid systems, and which key insights and implications have been extracted. Finally, we delve into the key advances necessary for the design of next generation biohybrid energy conversion systems.

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)0.003
metaresearch head score (Gemma)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.154
GPT teacher head0.344
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2021
Admission routes1
Has abstractyes

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