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DataSheet_1_Risk factors for metachronous esophageal squamous cell carcinoma after endoscopic or surgical resection of esophageal carcinoma: a systematic review and meta-analysis.docx

2023· dataset· en· W6946046395 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsIncidence (geometry)Funnel plotCarcinomaCancerEsophageal cancerEpidemiologyBasal cellHead and neck squamous-cell carcinoma

Abstract

fetched live from OpenAlex

Background<p>early-stage esophageal carcinoma (EC) patients lack typical clinical signs and symptoms and are often diagnosed and treated at a late stage, leading to a poor prognosis and a high incidence of metachronous esophageal squamous cell carcinoma (MESCC) and second primary carcinoma (SPC). The aims of the review were to identify and quantify risk factors for MESCC and analysis location of SPC in postoperative patients with EC; to predict incidence of MESCC over follow-up time.</p>Methods<p>an electronic search of studies reporting potential risk factors, the incidence of MESCC, and the location of SPC were performed on PubMed, Web of Science, Cochrane Library, Embase, and Scopus from inception to 10 November 2022. The Newcastle-Ottawa scale was used to assess the study quality, and the qualitative strength of evidence rating of all items was provided. The meta-regression model was used to predict the incidence of MESCC over follow-up time, the location distribution of SPC was presented using clustered column chart, while the publication bias was assessed using funnel plots and Egger’s test.</p>Results<p>smoking, age, history of multiple other cancer, and Lugol-voiding lesions (LVLs) were determined to be the risk factors of MESCC. LVLs were qualitatively determined as “definite” and the history of multiple other cancer as “likely.” The overall pooled MESCC incidence was 20.3% (95% CI: 13.8% to 26.8%), with an increase of 0.20% for each additional year of follow-up. The head and neck were the most common locations for SPC, followed by the esophagus.</p>Conclusion<p>timely investigating the age of patients, previous history of cancer and monitoring the number of LVLs in the first 5 years after operation are of great significance to identify high-risk populations of MESCC for timely medical care. Education and behavior correction about smoking are advocated. Tumor markers should be regularly detected in the head and neck, esophagus, and stomach. Endoscopic resection was associated with a higher incidence of MESCC, which provided a reference for doctors to choose the removal method.</p>Systematic review registration<p>https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022377030.</p>

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.940
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0820.000

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 head0.070
GPT teacher head0.301
Teacher spread0.231 · 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