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Record W2064225376 · doi:10.1136/jnnp-2014-308625

Hereditary spastic paraplegia: a novel mutation and expansion of the phenotype variability in SPG10: Table 1

2014· letter· en· W2064225376 on OpenAlexfundno aff
Laura Carosi, Temistocle Lo Giudice, Martina Di Lullo, Federica Lombardi, Carla Babalini, Fabrizio Gaudiello, Girolama Alessandra Marfia, Roberto Massa, Toshitaka Kawarai, Antonio Orlacchio

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2014
Typeletter
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsHereditary spastic paraplegiaBiologyGenetic heterogeneitySpasticityMovement disordersGeneticsPhenotypeNeuroscienceGeneMedicinePathologyPhysical medicine and rehabilitationDisease

Abstract

fetched live from OpenAlex

range 0-307), with a median citation rate of 3 per year (range 0-48.3).A literature review of UK medical meetings during a similar time period revealed variable rates of eventual publication.Weale et al 2 found publication rates of 24-54% across four surgical meetings.A study of emergency medicine identified a publication rate of 30%, with platform presentations more likely to be published.3 Oral and maxillofacial surgery abstracts from 2001 to 2007 were published in 24% of cases, with scientific versus clinical presentations more likely to achieve eventual publication.4 Urology abstracts from 2001 to 2002 were published in 42% cases.5 Strengths of our study include surveying a large number of abstracts, a relatively long follow-up time and a robust search methodology consistent with previous work on this subject.A potential limitation is that we were unable to determine how many abstracts were submitted for full publication but eventually rejected, or never submitted at all, as this would have required extensive surveying of all authors presenting at the ABN.Our findings emphasise the importance of collaborative work in achieving high-quality research and publication.However, it is possible that this represents a surrogate of other factors, for example case reports may be likely to be single-centre work.While impact factors are a controversial metric of research quality, the majority of eventually published work following presentation at the ABN contributed to the scientific literature in the form of subsequent citations.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.023
GPT teacher head0.239
Teacher spread0.216 · 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 designCase report
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

Citations16
Published2014
Admission routes1
Has abstractyes

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