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Record W2890700276 · doi:10.1111/arcm.12419

Raman Binary Mapping of Iron Age Ostracon in an Unknown Material Composition and High‐Fluorescence Setting—A Proof of Concept

2018· article· en· W2890700276 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArchaeometry · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
FundersEuropean Research CouncilTel Aviv UniversityAzrieli FoundationIsrael Science Foundation
KeywordsBinary numberRaman spectroscopyComposition (language)InkwellLegibilityFluorescenceComputer scienceArtificial intelligenceOpticsLiteratureMathematicsPhysicsArithmeticSpeech recognitionArtVisual arts

Abstract

fetched live from OpenAlex

The textual evidence from ancient Judah is mainly limited to ostraca, ink‐on‐clay inscriptions. Their facsimiles (binary depictions) are indispensable for further analysis. Previous attempts at mechanizing the creation of facsimiles have been problematic. Here, we present a proof of concept of objective binary image acquisition, via Raman mapping. Our method is based on a new peak detection transform, handling the challenging fluorescence of the clay, and circumventing preparatory ink composition analysis. A sequence of binary mappings (signifying the peaks) is created for each wavelength; their legibility reflects the prominence of Raman lines. Applied to a biblical‐period ostracon, the method exhibits high statistical significance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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