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Record W4386804086 · doi:10.23977/acss.2023.070611

The Construction and Research and Analysis of the Environmental Protection Platform of Old Things in Smart Campus

2023· article· en· W4386804086 on OpenAlexvenueno aff
Shun’an Xu, Xiaoxiao Guo

Bibliographic record

VenueAdvances in Computer Signals and Systems · 2023
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsnot available
FundersGovernment of Jiangsu ProvinceJiangsu University
KeywordsReuseProcess (computing)Resource (disambiguation)ArchitectureComputer scienceArchitectural engineeringEngineeringEngineering managementConstruction engineeringSystems engineeringGeographyWaste management

Abstract

fetched live from OpenAlex

With the in-depth development of environmental protection concept and smart campus, intelligent campus environmental protection has become an important issue. Through the analysis of existing research and platform cases, this paper proposes the architecture and functional modules of the old environmental protection platform of colleges and universities based on the concept of environmental protection, including article information release, old material recycling and resource reuse. At the same time, by analyzing the challenges faced in the process of platform construction, this paper proposes solutions, and verifies the effectiveness and feasibility of the smart campus old environmental protection platform through research and data analysis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.000
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 head0.020
GPT teacher head0.242
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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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