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Record W4382992030 · doi:10.59966/setyaki.v1i1.7

Manajemen Sains di Lembaga Pendidikan Islam

2023· article· en· W4382992030 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

VenueSETYAKI Jurnal Studi Keagamaan Islam · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Character Development
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPracticumDocumentationIslamQuality (philosophy)Medical educationPsychologyPedagogyComputer scienceMedicineGeography

Abstract

fetched live from OpenAlex

This article discusses science management in Islamic Education Institutions with a case study of MAN 4 Garut. The purpose of this research is to find out and describe science laboratory management. The techniques used in data collection are observation, interview, and documentation study. The results of this study show several stages in science laboratory management to improve the quality of learning at MAN 4 Garut. First, the planning stage. Second, the organizing stage. Third, the administration stage. Fourth, the funding stage. The inhibiting factors of science management include many expired substances, thus inhibiting the practicum process. The solution to obstacles in science laboratory management to improve the quality of learning is the need for evaluation every semester in the management of science laboratories.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.043
GPT teacher head0.350
Teacher spread0.307 · 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