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Record W1980923565 · doi:10.1577/m02-202

Construction of a Junction Box for Use with an Inexpensive, Commercially Available Underwater Video Camera Suitable for Aquatic Research

2004· article· en· W1980923565 on OpenAlexfundno aff
Steven J. Cooke, Christopher M. Bunt

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2004
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsnot available
FundersCampus Research BoardNatural Sciences and Engineering Research Council of CanadaIllinois Natural History Survey
KeywordsUnderwaterFlexibility (engineering)Computer scienceSoftware deploymentVideo cameraArtificial intelligenceOceanography

Abstract

fetched live from OpenAlex

Abstract Underwater video camera apparatus is an important fisheries research tool. Such cameras, developed and marketed for recreational anglers, provide an opportunity for researchers to easily obtain cost-effective and waterproof video apparatus for fisheries research. We detail a series of modifications to an inexpensive, commercially available underwater video camera (about US$125) that provide flexibility for deploying the equipment in the laboratory or in the field. Specifically, we describe the design of a junction box between the camera cable and the power supply and video feed that can be constructed for about $25. We also describe different deployment configurations and detail several examples of the data we have been able to collect using this technology.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.006

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 head0.049
GPT teacher head0.262
Teacher spread0.213 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations12
Published2004
Admission routes1
Has abstractyes

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