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Record W2223081114 · doi:10.1007/s10816-015-9271-x

Functionality and Morphology: Identifying Si Agricultural Tools from Among Hemudu Scapular Implements in Eastern China

2016· article· en· W2223081114 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Archaeological Method and Theory · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMorphology (biology)ChinaAgricultureGeographyComputer scienceBiologyAgroforestryEvolutionary biologyEcologyPaleontologyArchaeology

Abstract

fetched live from OpenAlex

Most Chinese archaeologists assume that the scapular implements used in the Hemudu culture in eastern China (7000–5000 BP) were the si agricultural implements (tools for breaking ground and turning soils over to assist in seeding) recorded in ancient Chinese literatures and, accordingly, assume the Hemudu culture was a farming society. However, ethnographic and historical literatures worldwide have suggested inconclusive functions for similar implements. We conducted a range of experiments under realistic conditions, including hide and plant processing and earth-working, followed by use-wear analysis, to identify the functions of the Hemudu scapular implements. The results suggest that no more than half of the implements were employed as si and that their penetrability and durability were rather limited. These findings help explain why Hemudu should not be labeled as a farming society. Through experimentation and use-wear analysis, we produced relatively large datasets that make a significant contribution to the identification of soil-derived wear patterns on bone tools. We also included quantitative measurements of soil properties to ensure similarities in use contexts between our experimental and archaeological analogies in order to reach reliable functional identifications. Our approaches and results, therefore, provided a solid base for re-evaluating previous research as well as building a standardized database of scientific value for future evaluation and adjustment, even if that future research is done in isolation and in different soil contexts.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.332
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it