MétaCan
Menu
← Back to cohort

Oxygen flowmeters: accuracy and precision in adult care

2019· article· en· W2991547523 on OpenAlexaboutno aff
Amanda Pagliocchi, Josy Davidson, Mariana Rodrigues Gazzotti, Amaro Oliveira, Oliver A. Nascimento, José Roberto Jardim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsnot available
Fundersnot available
KeywordsFlow measurementMedicineVolumetric flow rateReproducibilityAccuracy and precisionUltrasonic flow meterOxygen deliveryLimits of agreementFlow (mathematics)OxygenBiomedical engineeringNuclear medicineAnalytical Chemistry (journal)StatisticsMechanicsMathematicsChromatographyPhysicsChemistry

Abstract

fetched live from OpenAlex

Oxygen flowmeter is an equipment used to control oxygen flow delivery in patients undergoing oxygen therapy. Objective: To evaluate accuracy and precision of oxygen flowmeters used in adult care. Methods:In vitro experimental study that evaluated 160 oxygen flowmeters (Flow range 0 to 15L/min), without previous use, manufactured in eight different countries (Australia, Brazil, Canada, China, England, France, Italy and United States of América). Flowmeters were tested at four flow rates, 1, 3, 5 and 10 L/min, with three repeated measurements in each flow. During the tests, the flowmeters were connected to the gas system through a reduction valve and a flow analyzer (FlowAnalyzer™ PF-302; Imtmedical Ag. Buchs Switzerland). The float (metal sphere) of the flowmeter was set to zero and then was kept at the corresponding mark of the flow to be tested. Was considered accurate flowmeter that maintained the three measurements within a ±10% variation, and precise, flowmeter that present no difference greater than 10% among repeated measurements (1st vs 2nd, 1st vs 3rd, 2nd vs 3rd). Results: The accuracy percentage in the low-flows (1 and 3L/min) was significantly lower than in the high-flows (5 and 10L/min). Flowmeters samples showed high precision in all tested flows (65 to 100%), specially at flows rate 5 and 10L/min (100%). None of the set of the flowmeters met the ideal expectation of 100% combined of accuracy and precision flows in all four tested. Conclusion: None of the eight different countries samples presented accurate and precision for all four tested flows. The flowmeters precision percentage was high despite their low accuracy.

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)0.026
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Explore more

Same topicBlood transfusion and management→French-language works237,207→