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Record W4392568440 · doi:10.30598/pakem.3.2.179-183

PELATIHAN MEDIA PEMBELAJARAN MATEMATIKA BERBASIS ETNOMATEMATIKA BERBANTUAN SOFTWARE GEOGEBRA DI KECAMATAN PULAU LAKOR

2023· article· en· W4392568440 on OpenAlex
Michael Inuhan, Andy Sunder Keer Dahoklory, John Nandito Lekitoo, Karolina Rupilele, Ratnah Kurniati, Sigit Sugiarto

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

VenuePAKEM Jurnal Pengabdian Kepada Masyarakat · 2023
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsComputer scienceMathematics educationPsychology

Abstract

fetched live from OpenAlex

One area in Southwest Maluku Regency that still maintains the culture of its people is Lakor District. Parts of culture that are still maintained today are Lakor weaving, traditional houses, lutur, traditional games, traditional dances, and others. On the other hand, mathematics learning in schools does not accommodate these diverse cultures. Ethnomathematics learning is a way of utilizing local culture as a means of introducing mathematical material. Ethnomathematics-based learning training activities with the help of Geogebra software were carried out with a percentage of 98.83%. Based on 10 indicators of implementation, this training activity is in the very good category and helps teachers make learning more creative and innovative

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.094
GPT teacher head0.345
Teacher spread0.250 · 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