In‐depth study of a speiss/matte sample from Castillo de Huarmey, North Coast of Peru, and its implications for the pre‐Columbian production of arsenic bronze in the Central Andes
Bibliographic record
Abstract
Abstract This study aims to characterize the phase composition and chemistry of the speiss/matte sample from the Metallurgist's Burial at Castillo de Huarmey and to use the information derived from these analyses to infer the temperatures, furnace conditions, and ores associated with the smelting processes, which created the speiss/matte sample. For this purpose, a number of geochemical analyses were performed on the spies/matte fragment: analysis of the general chemical composition (handheld X‐ray fluorescence spectrometry [hhXRF], X‐ray photoelectron spectroscopy [XPS]), analysis of the chemical composition in the micro area (field emission scanning electron microscope with an energy dispersive spectroscopy detector [FE‐SEM‐EDS], field emission electron probe microanalysis [FE‐EPMA]), analysis of the mineral composition (X‐ray diffraction [XRD]), and analysis of the phase composition (Raman spectroscopy). Chemical and mineralogical analyses of the speiss/matte specimen determined that the specimen is composed of distinct arsenide, arsenate, sulfide, and glass phases. During the smelting process, the charge material consisted mainly of Cu, Fe, and As sulfides. Arsenopyrite is the most likely candidate as the mineral source of arsenic. In addition, temperatures of at least 1200°C were achieved during the smelting process, with smelting occurring over a relatively short timeframe given that effective density separation of speiss and matte phases was not achieved.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".