Evidence map›Paper›PMID 37448003›Full record

ArticleSensors (Basel, Switzerland)2023

Calibration Assessment of Low-Cost Carbon Dioxide Sensors Using the Extremely Randomized Trees Algorithm.

Tiago Araújo, Lígia Silva, Ana Aguiar, Adriano Moreira

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Metrological Characterization of Low-Cost COSensors (Basel, Switzerland) · 2026
    Article
  3. AI Methods in Sensor Calibration.Sensors (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Article
  6. Low-Cost COSensors (Basel, Switzerland) · 2024
    Article
  7. A Review of Gas Sensors for COSensors (Basel, Switzerland) · 2024
    Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tiago AraújoFederal Institute of Education, Science and Technology of Rio Grande do Norte (IFRN), Parnamirim 59124-455, Brazil.ORCID 0000-0002-1766-5768
Lígia SilvaCTAC Research Centre, University of Minho, 4800-058 Guimarães, Portugal.ORCID 0000-0002-0199-8664
Ana AguiarTelecommunications Institute, Engineering Faculty, University of Porto, 4200-465 Porto, Portugal.
Adriano MoreiraAlgoritmi Research Centre, University of Minho, 4800-058 Guimarães, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the monitoring of carbon dioxide is an important proxy to estimate the air quality of indoor and outdoor environments, it is essential to obtain trustful data from CO

Indexed as

Air PollutantsAir PollutionAlgorithmsCalibrationCarbon DioxideEnvironmental MonitoringOxidesAir PollutantsCarbon DioxideOxidescarbon dioxide sensorsenvironmental monitoringmachine learningsensor calibration

Identifiers

PMID37448003
PMCPMC10346366

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.