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Record W4200242504 · doi:10.3791/1161-v

Large Volume (20L+) Filtration of Coastal Seawater Samples

2009· article· en· W4200242504 on OpenAlex

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.

Bibliographic record

VenueJournal of Visualized Experiments · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFiltration (mathematics)Volume (thermodynamics)SeawaterEnvironmental scienceInletWater columnChromatographyPulp and paper industryEnvironmental engineeringHydrology (agriculture)ChemistryOceanographyGeologyEngineeringMathematics

Abstract

fetched live from OpenAlex

The workflow begins with the collection of coastal marine waters for downstream microbial community, nutrient and trace gas analyses. For this method, samples were collected from the deck of the HMS John Strickland operating in Saanich Inlet. This video documents large volume (≥20 L) filtration of microbial biomass, ranging between 0.22μm and 2.7μm in diameter, from the water column. Two 20L samples can be filtered simultaneously using a single pump unit equipped with four rotating heads. Filtration is done in the field on extended trips, or immediately upon return for day trips. It is important to record the amount of water passing through each sterivex filter unit. To prevent biofilm formation between sampling trips, all filtration equipment must be rinsed with dilute HCl and deionized water and autoclaved immediately after use. This procedure will take approximately 5 hours plus an additional hour for clean up.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.494

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 science0.0000.000
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 head0.044
GPT teacher head0.389
Teacher spread0.345 · 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