The Neolithic Settlement of Aknashen (Ararat valley, Armenia) : Excavation seasons 2004-2015
Bibliographic record
Abstract
The Neolithic settlement of Aknashen (Ararat valley, Armenia): excavation seasons 2004-2015 is the first monograph devoted to the Neolithic period in Armenia. The research is based on an Armenian-French project, in which specialists from Canada, Romania, Germany and Greece also participated. The volume concerns the natural environment, material culture and subsistence economy of the populations of the first half of the 6th millennium BC, who established the first sedentary settlements in the alluvial plain of the Araxes river. The thickness of the cultural layer of Aknashen (almost 5m), the extent of the excavated areas and the multidisciplinary nature of the research, confer great importance upon this site for the study of the Neolithic, both in Armenia and in the South Caucasus as a whole. The publication examines the similarities and differences that exist between the sites established in the 6th millennium in the basins of the rivers Araxes (Armenia) and Kura (Georgia and Azerbaijan), as well as parallels with contemporary cultures in Southwest Asia. It also examines questions concerning the characterisation and periodisation of the Neolithic in the central part of the South Caucasus, the emergence of a production economy (pottery, animal husbandry, etc.) and the Neolithisation of this region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".