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Record W4387805642 · doi:10.15294/inapes.v2i2.48852

Manajemen Kolam Renang di Kabupaten Kebumen Tahun 2020

2021· article· en· W4387805642 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

VenueIndonesian Journal for Physical Education and Sport · 2021
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessOperations managementEngineering

Abstract

fetched live from OpenAlex

The purpose of this study was to find out how to plan swimming pools in Kebumen Regency in 2020, To find out how to organize swimming pools in Kebumen Regency in 2020, To find out how to move swimming pools in Kebumen Regency in 2020, To find out how to supervise swimming pools in Kebumen Regency in 2020. 2020. This research is a qualitative research, the method used to collect data is interviews. The subjects in this study were the owners, managers and visitors of swimming pools in Kebumen Regency. The data analysis technique used is descriptive analysis in a narrative manner. Planning for swimming pool management in Kebumen Regency is done quite well, each swimming pool has a short, medium and long term plan. The organization of swimming pool management in Kebumen Regency is still not going well, some swimming pools do not have a management organizational structure. The implementation of swimming pool management in Kebumen Regency is going quite well, every employee and employee is working satisfactorily. Supervision carried out by swimming pool owners in Kebumen Regency is carried out by verbal coordination, reporting is carried out only based on bookkeeping.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.497

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 communication0.0000.000
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 head0.008
GPT teacher head0.281
Teacher spread0.274 · 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