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Record W3016491209 · doi:10.1136/jclinpath-2020-206451

<i>SMARCA</i> family of genes

2020· review· en· W3016491209 on OpenAlex
Runjan Chetty, Stefano Serra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Pathology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsGeneComputational biologyBioinformaticsGeneticsBiologyMedicine

Abstract

fetched live from OpenAlex

lead to loss of expression of their respective proteins within the nucleus and, as such have characterised a set of malignancies that are underpinned by SMARCA-deficiency.The morphology of these tumours ranges from small to large epithelioid cells, giant cells and rhabdoid cells. The rhabdoid cells are frequently present in these tumours but are not a sine qua non for the diagnosis. Most of these tumours are undifferentiated or dedifferentiated, high-grade pleomorphic carcinomas. Focally, areas of better differentiation can be seen. The initial description of a SMARCA4-deficient malignancy was the small cell carcinoma of the ovary, hypercalcaemic type. Subsequently, tumours fitting this characteristic morphology and immunophenotype have been described in the lung, thoracic cavity, endometrium and sinonasal tract, gastrointestinal tract and kidney. Immunohistochemical loss of SMARCA2 and SMARCA4 may occur concomitantly or independently of each other.SMARCA-deficient malignant tumours represent a unique subset of tumours with typical morphological and immunohistochemical findings.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.133
GPT teacher head0.460
Teacher spread0.327 · 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