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Record W6888782075 · doi:10.21966/6cz5-6d70

Hakai Water Properties Vertical Profile Data Measured by Oceanographic Profilers, Research

2021· dataset· en· W6888782075 on OpenAlexaff

Bibliographic record

VenueHakai Institute · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsTula Foundation
Fundersnot available
KeywordsTurbidityWater qualityData processingData qualityQuality (philosophy)Series (stratigraphy)

Abstract

fetched live from OpenAlex

Temperature, conductivity, dissolved oxygen, fluorescence, photosynthetic active radiation, and turbidity data collected from 2012 to present by the Hakai Institute in waters surrounding Calvert Island, Johnstone Strait, and Quadra Island areas. This dataset presents data collected by oceanographic profiler instruments (RBR XR-620, RBR Concerto, RBR Maestro, and Seabird SBE 19plus v2) which have been automatically processed by following respective manufacturer's guidelines (see Hakai Water Properties Profile Processing and QA/QC Procedure Manual). The provisional processed data are then quality controlled by applying a series of tests that are following the QARTOD standards and more tests specific to the Hakai Institute data (see Hakai Water Properties Profile Processing and QA/QC Procedure Manual). The research dataset provides a subset of the provisional dataset which has been manually reviewed and judged good for science quality level. Data were collected by the Hakai Institute Oceanography Program, the Nearshore Program, and the Juvenile Salmon Program.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient 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 score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0020.003
Open science0.0080.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.037

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 head0.252
GPT teacher head0.361
Teacher spread0.109 · 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
Published2021
Admission routes1
Has abstractyes

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