MétaCan
Menu
Back to cohort

Integrated assessment of heavy metal pollution in the great bačka canal: Comparing active and passive sampling methods

2024· article· en· W4405856414 on OpenAlexaff
Đorđe Pejin, Dragana Tomašević Pilipović, Slaven Tenodi, Brent G. Pautler, Alexander Sweett, Dejan Krčmar

Bibliographic record

VenueChemosphere · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Guelph
FundersFP7 Ideas: European Research CouncilScience Fund of the Republic of Serbia
KeywordsSampling (signal processing)Environmental sciencePollutionHeavy metalsEnvironmental chemistryEnvironmental engineeringChemistryEngineeringTelecommunications

Abstract

fetched live from OpenAlex

(geo-accumulation index) and IWCTU (interstitial water criteria toxic units), revealed low to moderate contamination levels. Although copper content classified the sediment as extremely polluted (195.7 mg/kg), its low bioavailability (16 μg/L in pore water) mitigates immediate ecological risks. These findings emphasize the importance of integrating passive sampling in regulatory frameworks for a realistic environmental risk assessment of sediments.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.042
GPT teacher head0.352
Teacher spread0.310 · 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 designBench or experimental
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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueChemosphereSame topicHeavy metals in environmentFrench-language works237,207