Personalized Gravestones: Your Life’s Passion for all to See and Hear
Bibliographic record
Abstract
In the past several years, a trend has developed that in an earlier age would have seemed inappropriate and perhaps even morbid; the increased personalization of gravestones (memorials). What makes this trend interesting is the variety of shapes, designs, manufacturing processes, and types of personalization actually appearing on gravestones, including seven-inch LCD (Liquid Crystal Display) screens recessed into the face of memorials. This paper discusses gravestones (memorials) in a religious context. It examines the rapidly developing market for elaborately designed memorials both in their traditional forms, typically vertical and created out of granite with just a name and date of death, to memorials in every conceivable size, shape and colour portraying scenes of the deceased’s everyday life. Although this paper concentrates on memorials found in Christian, mostly Catholic and Protestant cemeteries, references to personalization, or lack of it, in Jewish and Muslim cemeteries are also discussed. Briefly addressed are references to advances in the latest engraving processes that are now making these personalized memorials possible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.014 |
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".