THE FALERII NOVI PROJECT: THE 2023 SEASON
Bibliographic record
Abstract
A four-week campaign from 29 May–23 June 2023 marked the third season of the Falerii Novi Project, and the second season of stratigraphic excavation on site as part of an international collaboration between the British School at Rome, Harvard University, the Institute of Classical Studies (University of London) and the University of Toronto, along with researchers from Ghent University and the University of Florence, under the authorization of the Soprintendenza Archeologia, Belle Arti e Paesaggio per la Provincia di Viterbo e per l’Etruria Meridionale. The project, described in two previous reports (Bernard et al., 2022; Andrews et al., 2023b), sets out to explore the urban history of the site of Falerii Novi in the Middle Tiber Valley (Andrews et al., 2023a). Excavation concentrated on three areas of the city: work continued in Areas I (macellum) and II (domus), while Area III in the southern sector of the town was closed and a new Area V opened above a series of tabernae along the northwestern side of the forum piazza (Fig. 1). Reported elsewhere in this volume are other activities also undertaken under the broad umbrella of the Falerii Novi Project over the past year. These include a large geophysical survey of the suburban area begun with the aim of exploring the immediate hinterland of the city (Pomar, 2024) and a topographical reassessment of the open excavations conducted by the Soprintendenza between 1969 and 1974 (Fochetti, 2024).
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.085 | 0.038 |
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".