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Record W4234015955 · doi:10.1002/gea.21692

Issue Information

2019· paratext· en· W4234015955 on OpenAlexaboutno aff
Giuseppe Montana, Luciana Randazzo, Claudio Ventura‐Bordenca, Renato Giarrusso, Roberta Baldassari, Anna Maria Polito, Lea Obrocki, Hans-Joachim Eder, Franziska Gehrke, Andreas Lang, Timo Vö, Katharina Willershäuser, Dennis Rusch, Georgia Wilken, Erofi Li-Iris Hatzi-Spiliopoulou, Olympia Kolia, Meir Finkel, Ran Barkai, Avi Gopher, Erez Ben‐Yosef, Juan Antonio Quirós-Cas Llo, Cris Ano Nicosia, Michael Benede, Jonathan Haws, Nuno Bicho, Lukáš Friedl, Brooks B. Ellwood, Jacopo Bone, Guido Furlan, Simona Musazzi, Jiřı́ Svoboda, Oldřich Krejčí, Vladimíra Krejčí, Alena Dohnalová, Sandra Sázelová, Jarosław Wilczyński, Piotr Wojtal, Filippo Saiano, O Orino-Luca Pantani, Riccardo Scalenghe, Maxime Lamoureux‐St‐Hilaire, Marcello A. Canuto, E. Wells, Clarissa Cagnat, Tomás Barrientos Q., François Courchesne, Claude Chapdelaine, Lara Munro, Michael Kempf, Héloïse Barbel, Najat Bhiry, Dominique Todisco, Pierre Desrosiers

Bibliographic record

VenueGeoarchaeology · 2019
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsCitationComputer scienceInformation retrievalWorld Wide Web

Abstract

fetched live from OpenAlex

in 6 issues per year. Ins tu onal subscrip on prices for 2019 are: Print & Online: US$3,996 (US), US$3,996 (Canada and Mexico), 2,176 (UK), 2,746 (Europe), US$4,256 (Rest of World). Prices are exclusive of tax. Asia-Pacifi

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.076
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0100.006
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.9240.910

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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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