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Record W2043073752 · doi:10.1177/08830738050200100401

The Floppy Infant: Retrospective Analysis of Clinical Experience (1990—2000) in a Tertiary Care Facility

2005· article· en· W2043073752 on OpenAlexaffabout
Kirandeep Birdi, Asuri N. Prasad, Chitra Prasad, Bernard Chodirker, Albert E. Chudley

Bibliographic record

VenueJournal of Child Neurology · 2005
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicinePediatricsRetrospective cohort studyTertiary careMedical diagnosisSurgeryRadiology

Abstract

fetched live from OpenAlex

We describe the results of a retrospective study of floppy infants evaluated at the Children's Hospital of Winnipeg, a tertiary care children's facility. Cases were ascertained by a systematic search of clinical databases, hospital and electromyographic records for "floppy" infants age < 1 year, referred over a period of 11 years (1990-2000). Eighty-nine infants, 42 female (47.2%) and 47 male (52.8%), were included in the study. A definitive diagnosis was established in 60 (67.4%) cases, in 24 cases (40%) on purely clinical grounds, whereas in 36 (60%) cases, additional investigations were necessary. Karyotype, molecular diagnostics, cranial imaging, and muscle and skin biopsy provided diagnostic information. Genetic disorders in 18 of 60 (20.2%), congenital or acquired disorders of the central nervous system in 22 of 60 (24.7%), and disorders of the lower motor unit in 9 of 60 (10.1%) contributed to the majority of diagnoses. Eight of 89 (8.9%) infants died in the first year, and 2 of 89 (2.6%) were on home ventilation. Of the 61 infants surviving beyond 12 months, 38 of 61 (62.3%) were found to be globally delayed, and only 30 of 61 (49.2%) achieved independent ambulation at their last clinical evaluation. Systematic evaluation of a floppy infant followed by careful selection of investigations (karyotype, DNA-based diagnostic tests, and cranial imaging) can maximize diagnostic yield.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.362
Teacher spread0.345 · 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 teacher head, 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

Citations49
Published2005
Admission routes2
Has abstractyes

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