MétaCan
Menu
Back to cohort
Record W3190094972 · doi:10.1029/2020wr029083

A Simple Chamber Design for Calibrating Weiss Saturometers and Recommendations for Measuring and Reporting Total Dissolved Gases

2021· article· en· W3190094972 on OpenAlexaff
Naomi K. Pleizier, Steven J. Cooke, Colin J. Brauner

Bibliographic record

VenueWater Resources Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton UniversityUniversity of British Columbia
Fundersnot available
KeywordsCalibrationSupersaturationHydroelectricityEnvironmental scienceDownstream (manufacturing)Protocol (science)Computer scienceProcess engineeringPoint (geometry)Remote sensingHydrology (agriculture)ChemistryStatisticsEngineeringElectrical engineeringOperations managementGeologyMathematicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Total dissolved gas (TDG) supersaturation downstream of features such as hydroelectric dams can cause harmful bubbles to grow in the tissues of aquatic animals. TDG supersaturation is often measured using Weiss saturometers, but information on the calibration and use of these instruments is scarce in the literature. Regular calibration, accurate measurement procedures, and standardized TDG reporting are important for generating reliable measurements that are easily interpreted. We provide a description of low‐cost calibration equipment that practitioners can build themselves and recommend a specific two‐point calibration protocol. We also recommend methods for the more accurate measurement and reporting of TDG.

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)0.012
metaresearch head score (Gemma)0.023
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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.023
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0050.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.011

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 head0.163
GPT teacher head0.351
Teacher spread0.188 · 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
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

Citations12
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueWater Resources ResearchSame topicFish Ecology and Management StudiesFrench-language works237,207