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Record W2767294283 · doi:10.1186/s12889-017-4873-8

Correction to: The GREENH-City interventional research protocol on health in all policies

2017· erratum· en· W2767294283 on OpenAlexaff
Marion Porcherie, Zoé Vaillant, Emmanuelle Faure, Stéphane Rican, Jean Simos, Nicola Cantoreggi, Zoë Héritage, Anne Roué Le Gall, Linda Cambon, Thierno Diallo, Eva Vidales, Jeanine Pommier

Bibliographic record

VenueBMC Public Health · 2017
Typeerratum
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversité du QuébecUniversité Laval
FundersWorld Health Organization
KeywordsSpellingBiostatisticsMedicinePublic healthProtocol (science)Library scienceAlternative medicineLinguisticsPathologyComputer science

Abstract

fetched live from OpenAlex

After publication of the article [1], it has been brought to our attention that in the original publication the third author's name was spelt incorrectly. The correct spelling is "Emmanuelle Faure". This was previously spelt as "Emmannuelle Faure". The original article has been revised to reflect this.

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)0.051
metaresearch head score (Gemma)0.356
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: Protocol · Consensus signal: none
Teacher disagreement score0.245
Threshold uncertainty score0.821

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.356
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0030.004
Research integrity0.0060.014
Insufficient payload (model declined to judge)0.2450.072

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 head0.473
GPT teacher head0.532
Teacher spread0.059 · 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
GenreProtocol

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
Published2017
Admission routes1
Has abstractyes

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