BILANGAN KROMATIK LOKASI UNTUK GALAKSI DAN HUTAN LINIER
Bibliographic record
Abstract
Misalkan G = (V, E) graf terhubung dan c suatu k-pewarnaan dari G. Kelas warna pada G adalah himpunan titik-titik yang berwarna i, dinotasikan dengan Ci untuk 1 ≤ i ≤ k. Misalkan Π = {C1, C2, · · · , Ck} adalah partisi terurut dari V (G) berdasarkan pewarnaan titik, maka representasi v terhadap Π disebut kode warna dari v, dinotasikan dengan cΠ(v). Kode warna cΠ(v) dari suatu titik v ∈ V (G) didefinisikan sebagai vektork: cΠ(v) = (d(v, C1), d(v, C2), · · · , d(v, Ck)) dimana d(v, Ci) = min{d(v, x : x ∈ Ci)} 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). Galaksi adalah gabungan dari graf bintang. Hutan Linier adalah gabugan dari graf lintasan. Pada tulisan ini akan dibahas bilangan kromatik lokasi untuk Galaksi dan Hutan Linier.Kata Kunci: Kelas warna, Kode warna, Bilangan kromatik lokasi, Galaksi, Hutan Linier, Graf Bintang, Graf Lintasan Diterima : 29 November 20
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.022 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".