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Record W2071421734 · doi:10.1080/03632415.2013.838133

Smartphones and Digital Tablets: Emerging Tools for Fisheries Professionals

2013· article· en· W2071421734 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFisheries · 2013
Typearticle
Languageen
FieldComputer Science
TopicMobile and Web Applications
Canadian institutionsTrent UniversityCarleton University
Fundersnot available
KeywordsFisheryBusinessData scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

ABSTRACT Smartphones and digital tablets are used to collect data for agricultural, geographical, and medical research. Science professionals find these devices attractive because they contain many useful hardware accessories (e.g., camera, Global Positioning System [GPS], accelerometer) and the capacity to access and customize software applications (apps). To enhance student learning, some educators are also integrating tablets into curricula for both indoor and outdoor course work. Recently, fisheries professionals have begun using these devices for data collection and public outreach and awareness. With new waterproofing technology, cases, and peripheral adapters, smartphones and digital tablets are continually becoming more relevant for data collection and education in fisheries. Here, we synthesize some of the available information on smartphone and tablet use for data collection and education and explore some current uses and future opportunities for these devices in fisheries. Overall, our objective is to demonstrate that smartphones and digital tablets are useful tools for fisheries professionals, including technicians, managers, and educators. RESUMEN Los teléfonos inteligentes y las tabletas digitales se utilizan para colectar datos geográficos, de agricultura y de investigaciones médicas. Los profesionales de la ciencia encuentran atractivos estos dispositivos porque contienen accesorios útiles de hardware (p.e. cámaras, sistemas de posicionamiento geográfico –GPS-, acelerómetros, etc.) y además son capaces de brindar acceso y configurar aplicaciones de software (apps). Con el fin de mejorar el aprendizaje de los estudiantes, algunos educadores están integrando las tabletas digitales en las matrículas tanto dentro como fuera de los salones de clases. Recientemente, los profesionales de las pesquerías han comenzado a usar estos dispositivos para colectar datos, para difusión y concientización. Con nueva tecnología submarina, cubiertas y adaptadores periféricos, los teléfonos inteligentes y las tabletas digitales están volviéndose cada vez más relevantes para educación y para colectar datos pesqueros. En este estudio se resume parte de la información disponible en lo tocante al uso de teléfonos inteligentes y tabletas digitales con fines educativos y de recolecta de datos. También se exploran algunos usos actuales y oportunidades futuras que guardan estos dispositivos para la ciencia pesquera. El principal objetivo es demostrar que los teléfonos inteligentes y las tabletas digitales son herramientas útiles para los profesionales de las pesquerías, incluyendo técnicos, manejadores y educadores.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.239
Teacher spread0.219 · 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