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Record W2066088150 · doi:10.1159/000194669

Cerebral Blood Flow, Oxygen, Carbon Dioxide Tensions, and Blood Bicarbonate in Controlling Drive and Timing in Patients with Chronic Obstructive Pulmonary Diseases

2009· article· en· W2066088150 on OpenAlexaff
D. Patakas, Brian J. Sproule, D.D. Jones, L. Phillipow, G. Ziutas

Bibliographic record

VenueRespiration · 2009
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCarbon dioxideBicarbonateCerebral blood flowOxygenAnesthesiaBlood flowBlood gas analysisHypercapniaRespiratory systemIntensive care medicineCardiologyInternal medicineAcidosis

Abstract

fetched live from OpenAlex

In patients with chronic obstructive pulmonary disease, respiratory drive as estimated from occlusion pressures (PO.1 and PO.1/PCO2, cm H2O/mm Hg) and respiratory timing (T1, T1/TTOT) were predicted accurately by multiple regression analysis from the respiratory parameters PO2, PCO2, and blood HCO3 in conjunction with estimates of cerebral blood flow. We used four linear models to obtain essentially the same multiple correlation coefficient, indicating that these independent variables are all important factors in controlling both the drive and timing of respiration.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.218
Teacher spread0.209 · 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 designObservational
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

Citations2
Published2009
Admission routes1
Has abstractyes

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