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Record W7128327422

Theuse of newforms in recreationalactivitywith a focus on geocaching in " Česká Kanada"

2015· dissertation· cs· W7128327422 on OpenAlexaboutno aff
Jiří Jůda

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2015
Typedissertation
Languagecs
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationTourismPresentation (obstetrics)ConversationFocus (optics)Physical activityTask (project management)
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Recreational physical activity is of great importance to human health. Reduces the risk of disease and positively beneficial to the human body. Recreational physical activity is influenced by many factors, eg. Age, sex, place of residence, but also its form. OBJECTIVES: Create a project and presentation of a study on new forms of recreational physical activities focused on geocaching. METHODS: The research involved five families with children permanently living in the Czech Canada. Their task was a regular recreational tourism for the purpose of hunting caches. To obtain data was used informal conversation and as a complementary data collection and record sheet output questionnaire. RESULTS: All the families surveyed had a positive shift in recreational physical activity. The most common form of recreational physical activity was hiking as well as cycling. Thanks geocaching was for all investigated deepened relationship to nature and cultural sites.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.015
GPT teacher head0.295
Teacher spread0.280 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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