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A CONTRIBUTION TO TEACHING CHEMISTRY WITH ENVIRONMENTAL AWARENESS USING THE COMPOSITION AND SOME REACTIONS OF DOMESTIC WASTE

2008· article· en· W3197833760 on OpenAlexaff
Jaqueline Keiko TANIMOTO, Karla Amâncio Pinto Field’s

Bibliographic record

VenuePERIÓDICO TCHÊ QUÍMICA · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsGarbageDecompositionGreenhouse gasOrganic matterMethanePollutionEffluentWaste managementEnvironmental chemistryEnvironmental scienceCarbon dioxideComposition (language)ContaminationSlurryChemistryEnvironmental engineeringOrganic chemistryEngineeringEcology

Abstract

fetched live from OpenAlex

The garbage has caused several problems within a city, is the visual pollution, in addition to contamination from the decomposition of organic matter, which generates the effluent called slurry which contaminates the soil and water in addition to the emission of greenhouse gases such as methane, sulfidric acid, ammonia and carbon dioxide gas. Reflecting on the various problems in a city that affect the environment, propose to study the composition of the garbage generated in the home, and the reactions to the formation of the same, the decomposition of organic matter and environmental impacts. Therefore, the mini course can be well used by the students, who did not have a broad view of chemistry and its applications in daily life by increasing their knowledge conceptual, in addition to awakening the motivation through the same methods that interest them.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0260.007

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 head0.205
Teacher spread0.200 · 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
GenreMethods

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
Published2008
Admission routes1
Has abstractyes

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