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Record W3017353988 · doi:10.1021/acssuschemeng.0c01427

Sequential Ammonia and Carbon Dioxide Adsorption on Pyrolyzed Biomass to Recover Waste Stream Nutrients

2020· article· en· W3017353988 on OpenAlexaff
Leilah Krounbi, Akio Enders, Christopher Anderton, Mark Engelhard, Rachel Hestrin, Dorisel Torres-Rojas, James J. Dynes, Johannes Lehmann

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsCanadian Light Source (Canada)
FundersPacific Northwest National LaboratoryMaterials Research Science and Engineering Center, Harvard UniversityCornell Center for Materials ResearchBill and Melinda Gates FoundationSustainable Agriculture Research and EducationDivision of Materials ResearchU.S. Department of AgricultureNational Science Foundation
KeywordsCarbon dioxideBiomass (ecology)NutrientPyrolysisAdsorptionAmmoniaEnvironmental scienceEnvironmental chemistryWaste managementChemistryCarbon dioxide reformingPulp and paper industryAgronomyOrganic chemistrySyngasCatalysisBiology

Abstract

fetched live from OpenAlex

uptake. However, high ash contents as found in py-HSW hinder this mechanism.

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 score0.013
Threshold uncertainty score0.889

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)0.0000.000

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 head0.005
GPT teacher head0.179
Teacher spread0.173 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

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