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Record W4394111348 · doi:10.6084/m9.figshare.21534861

Water Quality Parameters for Nova Scotia.xlsx

2022· dataset· en· W4394111348 on OpenAlexaboutno aff
Sarah Kingsbury, Kaylee MacLeod, Linda M. Campbell

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaQuality (philosophy)Environmental scienceGeologyGeographyPhysicsArchaeology

Abstract

fetched live from OpenAlex

This is the master database created originally for the Chinese Mystery Snail Project by Sarah Kingsbury (n = 251). This database was generated from multiple datasets of freshwater ecosystem parameters. <br> This database was modified for examining water quality parameters and mercury biomagnification in Nova Scotia. This database does not reflect the entire range of water quality data available, as only data that may be of interest to mercury biomagnification rates in Nova Scotia were included in this set. Saltwater or brackish sites were excluded, as well as areas unsuitable for fishing (small streams, areas without fish, ornamental ponds, etc.) (n = 344). Data are only from 2000 - 2022, based on what was available at the time of compiling the dataset. <br> Disclaimer: This dataset was complied for two specific goals and may not be suitable for other projects. Please contact the creators for more information.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.958
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9860.029

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 head0.139
GPT teacher head0.352
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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