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Record W6936187686 · doi:10.57745/jk5na1

Touques_Dataset_2017.txt

2024· dataset· en· W6936187686 on OpenAlexaff

Bibliographic record

VenueRecherche Data Gouv France · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsShipping Federation of Canada
Fundersnot available
KeywordsFish <Actinopterygii>Observer (physics)Primary (astronomy)Filter (signal processing)

Abstract

fetched live from OpenAlex

Number of european eel migrating downstream counted at the Breuil en Auge dam on the Touques River in 2017 thanks to a video counter and to an acoustic camera C1St represents the number of individuals seen by the primary monitoring device (video counter) each time step t, C1S2St represents the number of fish seen by the two observation devices (video counter and acoustic camera) C1U2St represents the number of fish seen by the secondary observation device (acoustic camera) but unseen with the primary monitoring device (video counter) C1SFt the number of fish seen by the primary observer and detected by the filter, given it was recorded by the secondary observer, C1UFt The number of fish unseen by the primary fish counter but seen by the filter after the secondary observer

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.885
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1150.139

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 head0.439
GPT teacher head0.474
Teacher spread0.035 · 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.

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
Published2024
Admission routes1
Has abstractyes

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Same venueRecherche Data Gouv FranceFrench-language works237,207