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Record W1985394668 · doi:10.5539/ass.v10n14p1

Readiness of Young Malaysian Fishermen to Use Global Positioning System within the Fishing Operation

2014· article· en· W1985394668 on OpenAlexvenueno aff
Mohd Nizam Osman, Siti Zobidah Omar, Jusang Bolong, Jeffrey Lawrence D Silva, Hayrol Azril Mohamed Shaffril

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemFishingBusinessGeographyFisheryComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Global Positioning System or GPS is an advanced tool that has been widely used in a number of industries including fisheries industry. The main attempt of the present study has much to do with GPS as it aims to identify young Malaysian fishermen readiness to use GPS within their fishing operation. The study is quantitative in nature where a developed questionnaire was used to collect the required data. A total of 240 young fishermen aged between 15 to 40 years old from four fishing areas in Malaysia were selected as the respondents. Overall, it can be concluded that young Malaysian fishermen are ready to use GPS within their fishing operation. However, their readiness can be further improved if aspects such as financial affordability, number of agencies staff, availability of workshop repairing dysfunction GPS and access to GPS are considered by the related agencies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.740
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2014
Admission routes1
Has abstractyes

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