MétaCan
Menu
Back to cohort
Record W4411617395 · doi:10.51847/oxbxngs

10.51847/oxbxNgS

2000· article· en· W4411617395 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Environment
Canadian institutionsnot available
Fundersnot available
KeywordsSewageEnvironmental scienceSewage treatmentWaste managementPulp and paper industryEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

The present study deals with the evaluation the performance of 339 million liter per day (MLD) Sewage Treatment Plant located at Amberpet, Hyderabad which is based on Up-flow Anaerobic Sludge Blanket Process (UASB).Performance of this STP is an essential parameter which was measured by the quality of treated effluent discharged into Musi River.Sewage samples were collected fro m the influent and effluent of the treatment plant and analyzed for the physico-chemical and microbiological parameters, such as pH, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, total suspended solids, volatile fatty acids, alkalinity, sulphate, sulphide and fecal coliforms as per standard methods.The effluent sample showed more than 90% of impurities remova l by UASB technology, which indicates the better efficiency and performance of the STP.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.075
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9250.919

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 head0.196
Teacher spread0.187 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicRegional Development and EnvironmentFrench-language works237,207