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Record W6906451620 · doi:10.17632/36hgynt59n

Supplemental material

2020· dataset· en· W6906451620 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsJudgementCohortInformation biasRisk assessmentCohort studyQuality of evidenceQuality (philosophy)Systematic review

Abstract

fetched live from OpenAlex

Supplemental material for: Logger JGM, Olydam JI, Driessen RJB. Use of beta-blockers for rosacea-associated facial erythema and flushing: a systematic review and update on proposed mode of action. Supplemental Figure 1. Review author’s judgement about each risk of bias item for the included RCT (n=1) with the Cochrane Risk of Bias tool. Supplemental Figure 2A. Review author’s judgement about each risk of bias item for each included cohort study and case report/series (n=7) with the Quality in Prognosis Studies tool. Supplemental Figure 2B. Review author’s judgement about each risk of bias item presented as percentages across all included cohort studies and case reports/series (n=7) with the Quality in Prognosis Studies tool. Supplemental Table 1. Search strategy. Supplemental Table 2. In –and exclusion criteria. Supplemental Table 3. Review author’s judgement about each risk of bias item for the included case-control study (n=1) with the Newcastle-Ottawa scale.

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)0.005
metaresearch head score (Gemma)0.052
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.194
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.009
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8060.252

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 head0.087
GPT teacher head0.336
Teacher spread0.249 · 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
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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Same venueMendeley DataFrench-language works237,207