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Record W2913238166 · doi:10.25077/jmu.8.2.33-36.2019

BILANGAN KROMATIK LOKASI GRAF TAK TERHUBUNG DENGAN GRAF LINGKARAN SEBAGAI KOMPONEN-KOMPONENNYA

2019· article· id· W2913238166 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

VenueJurnal Matematika UNAND · 2019
Typearticle
Languageid
FieldComputer Science
TopicGraph Labeling and Dimension Problems
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Misalkan G = (V, E) suatu graf terhubung dan c suatu k-pewarnaan dari G. Kelas warna pada G adalah himpunan titik-titik yang berwarna i, dinotasikan dengan Si untuk 1 ≤ i ≤ k. Misalkan Π= {S1, S2, · · · , Sk} adalah partisi terurut dari V (G) berdasarkan pewarnaan titik, maka representasi v terhadap Πdisebut kode warna dari v, dinotasikan dengan cΠ(v). Kode warna cΠ(v) dari suatu titik v ∈ V (G) didefinisikan sebagai vektor-k:cΠ(v) = (d(v, S1), d(v, S2), · · · , d(v, Sk))dimana d(v, Si) = min{d(v, x) | x ∈ Si)}, untuk 1 ≤ i ≤ k. Jika setiap titik yang berbeda di G memiliki kode warna yang berbeda untuk suatu Π, maka c disebut pewarnaan lokasi untuk G. Jumlah warna minimum yang digunakan pada pewarnaan lokasi dari graf G disebut bilangan kromatik lokasi untuk G, dinotasikan dengan χL(G). Pada penelitian ini akan dibahas tentang penentuan bilangan kromatik lokasi pada graf prisma berekor.Kata Kunci: Bilangan Kromatik Lokasi, Graf Tak Terhubung, Graf Lingkaran, Komponen

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.011
GPT teacher head0.218
Teacher spread0.207 · 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