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Record W4313731696 · doi:10.15627/jd.2022.21

Editorial Board to volume 9, issue 2

2022· paratext· en· W4313731696 on OpenAlexaff
Irfan Ullah, Yuehong Su, Umberto Berardi, Szybinska Barbara, Manuel Arsenio, Barbón Álvarez, Valerio Roberto, Maria Lo Verso, Paola Sansoni, Boon Lim, S. Lagüela, Canan Kandilli, Guiqiang Li, Ferdinando Salata, Manuel Antonio, Fabio Peron, Lambros Τ. Doulos, Alp Tural, Shen Hui, Marina Bonomolo, Yaik-Wah Lim, Ahmed Freewan, Rizki A. Mangkuto, Petar Pejić, Mohammed Mayhoub, Mustafa Karam, Jian Yao, Hui Lv, Vincenzo Costanzo, Osama Omar, Francesco Nocera, Paula Esquivias, Doris Abigail, Chi Pool, Feride Yılmaz, Banu Manav, Peng Xue, Omid Nematollahi, Seyed Mohammad Hosseini, Wei Wang

Bibliographic record

VenueJournal of Daylighting · 2022
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVolume (thermodynamics)Environmental scienceThermodynamicsPhysics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.017
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.248
Threshold uncertainty score0.830

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.001
Scholarly communication0.0130.004
Open science0.0030.002
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.2480.162

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 head0.023
GPT teacher head0.230
Teacher spread0.207 · 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
GenreEditorial

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
Published2022
Admission routes1
Has abstractno

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