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Record W2463558705 · doi:10.1186/s40880-016-0127-x

Relapse of both small cell lung cancer and Lambert–Eaton myasthenic syndrome after a 13-year disease-free survival period

2016· article· en· W2463558705 on OpenAlexaff
Fumio Asano, Keisuke Watanabe, Masaharu Shinkai, Yoshitaka Tei, Kei Mishina, Mikiko Tanabe, Hiroshi Ishii, Masahiro Shinoda, Tadasuke Shimokawaji, Makoto Kudo, Takeshi Kaneko

Bibliographic record

VenueChinese Journal of Cancer · 2016
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineLambert-Eaton myasthenic syndromeChemoradiotherapyDiseaseRadiation therapyStage (stratigraphy)SurgeryInternal medicineLung cancerOncologyMyasthenia gravis

Abstract

fetched live from OpenAlex

Lambert-Eaton myasthenic syndrome (LEMS) is a paraneoplastic syndrome and only 3% of small cell lung carcinoma (SCLC) patients have LEMS. Moreover, the recurrence of SCLC after a disease-free survival (DFS) of more than 10 years is rare. We report a patient who had a recurrence of both SCLC and LEMS after a 13-year DFS period. A 69-year-old man was diagnosed with LEMS and SCLC (cT0N2M0, stage IIIA) 13 years ago. Chemoradiotherapy was performed and a complete response was achieved. With anticancer treatment, the LEMS symptoms was alleviated. At the age of 82 years, gait disturbance appeared followed by left supraclavicular lymphadenopathy and further examination revealed the recurrence of SCLC. Careful screening for the recurrence of SCLC might be needed when the patient has recurrent or secondary paraneoplastic neurological syndrome even after a long DFS period.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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