MétaCan
Menu
Back to cohort
Record W2099389385 · doi:10.1109/iembs.2007.4353473

Low-order parametric system identification for intrapartum uterine pressure-fetal heart rate interaction

2007· article· en· W2099389385 on OpenAlex
Philip Warrick, Robert E. Kearney, Doina Precup, Emily Hamilton

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConference proceedings · 2007
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMcGill University
Fundersnot available
KeywordsImpulse responseParameterized complexityFetal heart rateParametric statisticsMathematicsLeast-squares function approximationSingular value decompositionStandard deviationHeart rateStatisticsAlgorithmMedicineApplied mathematicsBlood pressureInternal medicineMathematical analysis

Abstract

fetched live from OpenAlex

For uterine pressure-fetal heart rate data collected during labour and delivery, we first identify the impulse response function (IRF) by least squares. We then use singular value decomposition of this noisy least-squares estimate and an order-reduction search to obtain an improved order estimate compared to that based on the standard minimum-description length (MDL). This ;cleaner' IRF is succinctly parameterized by fitting it with a second-order dynamic model. Using standard hypothesis tests, the model coefficients show statistically significant differences between normal and pathological cases.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.307
Teacher spread0.281 · 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