MétaCan
Menu
← Back to cohort
Record W4379661961 · doi:10.2166/9781789063738_0103

基于微生物电化学技术平台的碳增值

2023· book-chapter· zh· W4379661961 on OpenAlexaff
Jayesh M. Sonawane, Zhiyong Jason Ren, Deepak Pant

Bibliographic record

VenueIWA Publishing eBooks · 2023
Typebook-chapter
Languagezh
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBlueprintWater sectorReuseLow-carbon economyBusinessRenewable energyEnergy sectorNeutralityResource (disambiguation)Environmental economicsEngineeringGreenhouse gasPolitical scienceEconomicsComputer scienceWaste managementEnvironmental engineeringWater supplyMechanical engineering

Abstract

fetched live from OpenAlex

全球 CO2 排放量已增加到约 355 亿吨, CO2 的捕获和利用成本很高(MacDowell et al., 2017)。与此同时,城市固体废物 (20.1 亿吨)和污水(约 1000 km 3 )等大量含有机碳的废物流也因高昂的处置 和

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0380.016

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 head0.047
GPT teacher head0.216
Teacher spread0.169 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueIWA Publishing eBooks→Same topicWater-Energy-Food Nexus Studies→French-language works237,207→