Bibliographic record
Abstract
The remains of ancient communities have been found at Wadi Ramm and Humayma, Jordan in the midst of what is now the Jordanian desert. In past times these sites were located along caravan routes and were populated by Nabataean, Roman, Byzantine, and early Islamic peoples. Despite the fact that these sites are located tens of kilometers from the seashore, seashells are frequently found in the layers associated with the different population groups. As of yet, shells from the 1996-1997 excavations at Wadi Ramm and from the 2008-2010 excavations at Humayma have not received in depth analyses allowing them to be correctly identified, quantified, and associated with significant archaeological contexts. Archaeomalacology (the study of molluscs in archaeological contexts) is a vital part of deciphering ancient human diet and activity. It is also critical in determining past environments and transportation systems. Clearly these shells came from the sea, but how did they get to these remote desert locales? Based on the preliminary descriptions provided by the field excavators, the photographs of the Wadi Ramm shells, and the actual Humayma shells which are at Queen’s, I am creating a catalogue to identify, describe, and quantify the variety of mollusc species present. This catalogue incorporates all of the significant data in one place, thus allowing me to look for patterns in the frequency, condition, and probable function of the shells. This analysis will lead to a better understanding of the diet and cultural practices of the different ancient inhabitants at Wadi Ramm and Humayma.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".