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Record W2352495141

CT Diagnosis of Peripheral Small Lung Cancer

2010· article· en· W2352495141 on OpenAlexaboutno aff
Pan Lizhou

Bibliographic record

VenueChina Foreign Medical Treatment · 2010
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLung cancerRadiologyThin layerLungSign (mathematics)Differential diagnosisPleural cavityLayer (electronics)PathologySurgeryComposite materialInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective Through to periphery small lung cancer sign analysis,appraisal basic sign and other signs to its diagnosis application value.Methods The periphery small lung cancer which confirmed to 57 example pathology carries on the analysis. And ordinary CT thin layer (3mm) scans 11 examples; Screw CT convention adds the thin layer scanning(level thick 3mm,enters bed speed is 3mm/s,reconstructs 3mm) 25 examples,the convention raises resolution CT scanning(level thick 1mm,spacing 3mm) 12 examples,conventional Canada strengthens 9 examples.Results The surroundings small lung cancer sign includes:The burr drafts,accounts for 89.5%; The sublobe drafts,accounts for 86.0%; The pleural membrane drafts hollowly,accounts for 80.7%; The blood vessel gathers drafts,accounts for 56.1%; The vacuole drafts,accounts for 57.9%; The cavity drafts,accounts for 5.3%; The bronchial tube gasification drafts,accounts for 22.8%; The lump stove pleural membrane side strip laminated shape shade,accounts for 22.8%; The drainage bronchial tube interruption drafts,accounts for 7.0%; The ground glass drafts,accounts for 1.8%. Conclusion Scans or high resolution C with the thin layer the Tscanning is periphery the small lung cancer diagnosis and the differential diagnosis important method.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.014
GPT teacher head0.309
Teacher spread0.295 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2010
Admission routes1
Has abstractyes

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