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Record W2326667431 · doi:10.21037/atm.2016.03.17

Perspective on malignant pleural mesothelioma diagnosis and treatment

2016· article· en· W2326667431 on OpenAlexfundno aff
Ori Wald, David J. Sugarbaker

Bibliographic record

VenueAnnals of Translational Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMedicineChemotherapyMalignancyStage (stratigraphy)MesotheliomaDiseaseOncologyInternal medicinePleural diseaseSurgeryRespiratory diseaseLungPathology

Abstract

fetched live from OpenAlex

Malignant pleural mesothelioma (MPM) is an aggressive solid malignancy with dismal prognosis. The majority of newly diagnosed MPM patients present with advanced (IMIG/UICC stage IV) disease and are therefore treated with chemotherapy and supportive measures. The median survival of this group of patients ranges from 12 months with chemotherapy to 7 months with supportive care (1,2). Nonetheless, for a selected group of patients that present with a locally advanced disease (IMIG/UICC stage I–III), a personally tailored multimodality therapeutic (MMT) protocol comprising of cyto-reductive surgery and chemotherapy with or without radio-therapy may be the best therapeutic option. Although MMT is also associated with high rates of morbidity and mortality, it remains the sole option to significantly extend the survival of patients that physically and clinically qualify for this aggressive treatment strategy (3-8) .

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0130.005

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 head0.085
GPT teacher head0.360
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations9
Published2016
Admission routes1
Has abstractyes

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