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Ḥuqoq – 2023

2024· article· en· W4414519326 on OpenAlexaboutno aff
Jodi Magness, Dennis Mizzi, Matthew Grey, Jocelyn Burney, Martin T. Wells, Karen Britt, Ra‘anan Boustan

Bibliographic record

VenueḤadašŵt ʾarkeyŵlŵgiyŵt. · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsChapelGriffinExcavationEleventhLiberal arts educationWest virginia

Abstract

fetched live from OpenAlex

From 29 May to 4 July 2023, the eleventh season of excavations was conducted at H orbat H uqoq (henceforth H uqoq) in eastern Galilee (License No. G-1/2023; map ref. 24500–50/75430–65; Magness 2012 ; Magness et al. 2013 ; 2014 ; 2016a ; 2016b ; 2017 ; 2018 ; 2019 ; 2020 ; 2023 ). The excavation was undertaken and underwritten by the University of North Carolina (UNC) at Chapel Hill, Austin College (Texas), Brigham Young University (Utah), and the University of Toronto (Canada). Additional funding was provided by the Kenan Charitable Trust; the College of Arts and Sciences and the Carolina Center for Jewish Studies at UNC-Chapel Hill ; and private donors. The excavation was directed by J. Magness, with D. Mizzi (assistant director and finalizing of plans); M. Golan (administration); M. Grey and J. Burney (area supervision); J. Haberman (field photography); M. Robinson-Mohr (registration); D. Schindler (ceramics); C. Swan (glass); K. Britt and R. Boustan (mosaics); M. Wells (architecture); S. O’Connell (painted plaster); R. Mohr (drawing); V. Pirsky (drafting); C. De Brer (site conservation); M. Lavie (small finds conservation); and Griffin Higher Photography (aerial photography). The volunteers consisted of undergraduate and graduate students from the U.S.A., Canada, Germany and Slovakia.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.214
Threshold uncertainty score0.717

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2140.043

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 head0.022
GPT teacher head0.212
Teacher spread0.190 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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