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Record W2806336174 · doi:10.5430/jhm.v4n1p1

AML Subtype M5 Linked to Pulmonary Leukemic Infiltrates and Respiratory Failure and the Importance of Early Induction Chemotherapy

2018· article· en· W2806336174 on OpenAlexvenueno aff
Yvonne I. Chu

Bibliographic record

VenueJournal of Hematological Malignancies · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineChemotherapyLungInduction chemotherapyBiopsyLung biopsyMyeloid leukemiaPathologyLeukemiaInternal medicine

Abstract

fetched live from OpenAlex

Currently there are no practice guidelines for evaluating lung infiltrates in patients with newly diagnosed acute myeloid leukemia (AML). More specifically, it remains unclear if there is a need to obtain a lung tissue biopsy prior to the initiation of induction chemotherapy. This clinical question is particularly important in instances in which obtaining a lung tissue diagnosis can potentially delay anti-leukemic treatment. Here we describe a case of such lung infiltrates in which a newly diagnosed AML patient underwent a diagnostic lung biopsy before receiving chemotherapy, was shown to have leukemic infiltration of lung tissue, and subsequently had complete resolution of lung infiltrates following initiation of chemotherapy.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.296
Teacher spread0.267 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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