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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 OpenAlexaff
Michael Inuhan, Andy Sunder Keer Dahoklory, John Nandito Lekitoo, Karolina Rupilele, Ratnah Kurniati, Sigit Sugiarto

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0600.010

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

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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2023
Admission routes1
Has abstractyes

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