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Record W2775659283 · doi:10.1097/mph.0000000000001013

Spontaneous Regression in a Patient With Infantile Fibrosarcoma

2017· article· en· W2775659283 on OpenAlexaff
Sameer Farouk Sait, Enrico Danzer, Daniel C. Ramirez, Michael P. LaQuaglia, Meyers Paul

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsPediatric Oncology Group
FundersNational Cancer Institute
KeywordsMedicineFibrosarcomaWatchful waitingRegressionSpontaneous remissionTrunkBiopsySurgeryPediatricsRadiologyCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

Infantile fibrosarcoma usually presents as a rapidly growing mass on the extremities or trunk. We describe spontaneous regression in a 5-month-old female infant with biopsy proven, molecularly confirmed, right leg infantile fibrosarcoma currently at 26 months of age with no signs of local recurrence. Previously reported cases of spontaneous regression are reviewed, suggesting a benign clinical course in some cases. Although evidence for spontaneous regression is anecdotal in this rare tumor type, physicians should weigh the risks and benefits of surgery and chemotherapy against watchful waiting.

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)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.318
Teacher spread0.301 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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