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Record W6926168753 · doi:10.21966/yk87-4x24

High-resolution record of sea surface nitrate at Sentry Shoal in the Northern Strait of Georgia, British Columbia, Canada from 2015 to 2017

2019· dataset· en· W6926168753 on OpenAlexaboutno aff

Bibliographic record

VenueHakai Institute · 2019
Typedataset
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsSpring (device)ShoalMooringBiogeochemical cycleShoreNitrateSalinity

Abstract

fetched live from OpenAlex

The Environment Canada weather mooring at Sentry Shoal in the Northern Strait of Georgia provides a platform of opportunity for collection of high frequency biogeochemical measurements. From spring to fall in 2015, 2016, and 2017, autonomous sensors were deployed on the mooring to collect surface nitrate, temperature and salinity measurements every 30 minutes. Nitrate concentration was measured using a Satlantic SUNA (Ultraviolet Nitrate Analyzer), temperature and salinity were measured using a SeaBird 37-SMP MicroCAT. Sensors were deployed each year in the spring and serviced in the field every 2-3 months, following recovery in the fall, sensors were shipped for factory service and calibration. This project was supported by the Tula Foundation and the Pacific Salmon Foundation, fieldwork was a collaborative effort between the Hakai Institute, and SeaThis Consulting.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.036
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.007

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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