Sweating the Small Stuff Microdebris Analysis at Tell eṣ-Ṣâfi/Gath, Israel
Bibliographic record
Abstract
Most modern excavations intensively collect data from flotation, including both light and heavy fractions. While the light fraction (floated) is usually extensively analyzed by archaeobotanists, the heavy fraction or microdebris is often ignored or minimally examined since it requires intensive efforts at the microscopic level to recover and identify the remains. In recent years, a few studies have demonstrated the utility of intensive examination of the microdebris from archaeological sites as a means for investigating behavior on the microscopic level. When collected systematically across surfaces, the analysis of microdebris allows for the identification of different activities and deposits that are often less visible with macroscopic remains. This paper describes the goals and collection methods for microdebris analysis and presents some preliminary analysis of the microdebris from the excavations of the Early Bronze III nonelite residential neighborhood at Tell eṣ-Ṣâfi/Gath, Israel. The results demonstrate that various types of materials are deposited differentially between depositional contexts. Some types of deposits yield very little microdebris (e.g., alleyways), while others are characterized by their abundance (e.g., room interiors). Consequently, the systematic collection and analysis of contextually differentiated microdebris samples from across archaeological surfaces can help guide excavation strategies since it allows for certain deposits to be clearly targeted for intensive examination..
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.001 |
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 teacher head, 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".