MétaCan
Menu
Back to cohort
Record W2463366018 · doi:10.1016/0967-0653(96)83306-0

10.1016/0967-0653(96)83306-0

2000· article· en· W2463366018 on OpenAlexvenueno aff
M. Ganesan, L. Kannan

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsAlgaeMonsoonSedimentSeawaterManganeseOceanographyEnvironmental scienceSalinitySeasonalityPollutionEnvironmental chemistryBiologyGeologyBotanyChemistryEcology

Abstract

fetched live from OpenAlex

Seasonal variation in Fe and Mn concentrations were determined in seawater, sediment and algae (Padina gymnospora and Acanthophora spicifera) in the vicinity of Tuticorin port. Fe and Mn were appreciably higher than other parts of the Indian coast. High content of Fe and Mn were observed in seawater during northeast monsoon (November and December) and postmonsoon (January and March) seasons and in sediment Fe and Mn concentrations were high during monsoon (July to October) and postmonsoon (January, Feberuary) seasons due to increasing inputs of land runoffs. Algae also concentrated more metals during monsoon and postmonsoon seasons. Significantly higher Fe concentration in algae than other parts of the Indian coast reflects the intensity of Fe pollution in Tuticorin coast.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.011
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0030.004
Scholarly communication0.0050.008
Open science0.0050.005
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.9890.991

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 head0.006
GPT teacher head0.169
Teacher spread0.163 · 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

Citations10
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueTime to knitSame topicHeavy metals in environmentFrench-language works237,207