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Record W2000038728 · doi:10.5539/ep.v4n2p42

Interactive Web-Based Visualization for Lake Monitoring in Community-Based Participatory Research: A Pilot Study Using a Commercial Vessel to Monitor Lake Nipissing

2015· article· en· W2000038728 on OpenAlex
Mark P. Wachowiak, Renata Wachowiak-Smolíková, Brandon T Dobbs, James G. Abbott, Daniel F. Walters

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Pollution · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsNipissing University
FundersNatural Sciences and Engineering Research Council of CanadaNipissing University
KeywordsCitizen journalismGovernment (linguistics)Presentation (obstetrics)VisualizationIdentification (biology)Environmental planningEngineeringEnvironmental resource managementWorld Wide WebComputer scienceGeographyEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Environmental and limnological monitoring is of interest to government agencies, researchers, and the general public. In communities that rely on and are heavily affected by lakes and their watersheds, accessible and intuitive presentation of lake properties influences and aids decision-making, interventions, and the formulation of environmentally sound policies. In this paper, interactive web-based visualizations are employed as a mechanism to communicate environmental information collected from a commercial cruise vessel. A pilot study is presented for monitoring Lake Nipissing, a large culturally and environmentally important lake in northeastern Ontario, Canada. This example of community-based participatory research suggests that: (1) policy makers and researchers can quickly gain insight into what is happening in the lake through visualizations, which helps to direct subsequent, detailed investigations; and (2) through accessible, visual presentation, community members may be encouraged to become involved in contributing to environmental policies that directly affect them, thereby supporting environmental “citizen science”.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.360
GPT teacher head0.416
Teacher spread0.057 · 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