COMPARATIVE ANALYSIS OF MARKOV CHAIN MODEL ESTIMATION METHODS BASED ON VISUAL INSPECTION DATA
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.
Bibliographic record
Abstract
社会基盤施設の統計的劣化予測では，目視点検データを用いてマルコフ推移確率を推定し，マルコフ連鎖モデルにより劣化過程を記述する方法論が多く提案されているが，各種推定手法の有効性や適用可能性について実データを用いた比較事例は少ない．したがって，実務においてアセットマネジメントを実践する際に劣化予測手法の選択基準が明確であるとは言い難い．また，推定手法には，実務者が自ら適用するにあたって，数学的・技術的な障壁を有する手法が存在する．本研究では，各種推定手法の特長や制約条件について既往研究をもとに整理する．その上で，実点検データを用いて，想定される条件下においてマルコフ推移確率を推定し，各種手法が有効的に機能する条件や，適用が不適切になり得る状況を分析する．
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it