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Record W4229620743 · doi:10.1002/0471463736.tnmp23

Lung Cancer

2003· other· en· W4229620743 on OpenAlexaffabout
Michael Brundage, William J. Mackillop

Bibliographic record

VenueTNM Online · 2003
Typeother
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsLung cancerMedicinePathognomonicCancerDiseasePopulationLungOncologyInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Lung cancer is best conceptualized as a group of heterogeneous clinical entities with common molecular and cellular origins, but with different clinical behaviors, and hence, different prognoses. Lung cancer has a major impact on population health; taken together, lung cancers are the most common cause of cancer death in both males and females in North America. Overall, only 13% of patients survive more than 5 years after being diagnosed. Determining the prognosis for an individual patient with lung cancer is difficult, in part, because the clinical course of the disease in the individual case can evolve along a seemingly infinite combination of branching pathways. Over 90% of lung cancer patients present with signs or symptoms of disease, and since no symptoms or signs are pathognomonic for lung cancer, the disease has a capacity clinically to mimic other cancers and other nonmalignant diseases with a constellation of possible presenting symptoms. These varying presentations, and potential clinical evolutions, are in turn due to the multiple potential manifestations of the primary tumor, metastatic sites of involvement, and paraneoplastic syndromes. Despite the heterogeneity of the clinical manifestations of lung cancer, the prognosis for a population of patients with lung cancer is remarkably predictable. The overall mortality rates for lung cancer in North America over the last 15 years have remained unchanged. A population‐based study of over 12,000 patients with unresected non‐small‐cell lung cancer registered in seven Ontario Regional Cancer Centers (1982–1991) demonstrated no significant differences in patient survival either between Centers or over time. The predictability of population survival outcomes is of limited usefulness, however, due to the marked heterogeneity of patients making up the overall population. Prognostic factors are thus used to divide the overall population of lung cancer patients into subgroups in order to realize the benefits of prognostic stratification. A number of studies have addressed the identification and application of such factors.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.158
Threshold uncertainty score0.528

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1580.110

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 head0.015
GPT teacher head0.349
Teacher spread0.335 · 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
GenreOther

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

Citations0
Published2003
Admission routes2
Has abstractyes

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