Human-Climate Connection in North Central Iran Between 6000 and 2700 BCE
Bibliographic record
Abstract
During the Holocene, man’s challenges with climate entered a new phase. Holocene climatic cycles, by creatingdry events, have imposed many subsistence tensions on water-dependent communities. The semi-arid and aridregion of North Central Iran, which has been very vulnerable to any climate change, experienced unfavorableenvironmental conditions during these climatic events. So far, only a handful of Early Holocene rural settlementshave been found in the region, possibly because of the mostly arid climate of the period. In general, the firstevidence of Neolithic villages in North Central Iran dates back to the beginning of the Middle Holocene, afterthe 8.2 ka BP event. The first cultural flourishing of this region can be seen from the last quarter of the sixthmillennium BCE. Each cultural flourishing period seems to have declined for some time with the occurrence ofa dry event. The effects of climatic tensions on human societies in North Central Iran have been found around6500-6000, 5700-5400, 5000-4700, 4300-4000, and 3300-2700 BCE. According to data analysis, the frequency ofsettlements and the trend of cultural progress gradually peaked from the early sixth millennium to the mid-fourthmillennium BC, but in the second half of the latter millennium, a gradual decline began which led to the BronzeAge collapse in ca. 2700 BCE. This event probably occurred due to the drop in temperature and the increase in thefrequency and severity of aridity in the transition phase to the Late Holocene.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".