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Record W4385800695 · doi:10.36227/techrxiv.23900127

Sustainable Waste: Biomimetic Solutions For Medical and Food Waste Management Systems in the United States

2023· preprint· en· W4385800695 on OpenAlexaff
Priti See

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsNuclear Waste Management Organization
Fundersnot available
KeywordsBiomimeticsFood wasteBusinessSustainabilityEngineeringSustainable developmentWaste managementNanotechnologyPolitical scienceEcologyMaterials science

Abstract

fetched live from OpenAlex

<p>This paper explores the potential of biomimetics to revolutionize medical and food waste management systems in the United States. By forging circular economies in these fields, biomimetics can provide robust financial benefits. Furthermore, biomimetics can mitigate waste accumulation and related health hazards from such systems. In light of this paper’s findings, ongoing and long-term financial investments in biomimetic technology are recommended to create sustainable medical and food waste systems on a nationwide scale.</p>

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.053
GPT teacher head0.307
Teacher spread0.255 · 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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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