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Record W6948704264 · doi:10.5066/p97dz1as

Lake Ontario April Prey Fish Bottom Trawl Survey, 1978-2022

2022· dataset· en· W6948704264 on OpenAlexaffabout

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2022
Typedataset
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsMinistry of Energy, Northern Development and MinesMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsFish <Actinopterygii>PredationSpring (device)Sampling (signal processing)Forage fish

Abstract

fetched live from OpenAlex

This data release includes Lake Ontario prey fish data including species captured, relative abundance, spatial distribution, size structure, and age data from the April or spring prey fish bottom trawl survey, 1978 through 2022. Data from 1978 - 2015 are from U.S. waters of Lake Ontario while data from 2016 - 2022 include both U.S. and Canadian waters of Lake Ontario. Details about the vessel and gear descriptions, sampling protocols, and catch processing protocols are provided in the associated metadata. Portions of this data release follows the data model of the USGS Great Lakes Science Center Research Vessel Catalog (RVCAT). The trawl data included in this data release are a subset of the larger RVCAT data base. The RVCAT data can be found here: https://doi.org/10.5066/F75M63X0.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.012
Open science0.0060.006
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0480.001

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 head0.052
GPT teacher head0.275
Teacher spread0.223 · 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 teacher head, not a consensus.

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
Published2022
Admission routes2
Has abstractyes

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