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Record W3126499918

Usporedba protokola kontrole kvalitete mamografskih uređaja u Republici Hrvatskoj s protokolima u drugim državama

2020· dissertation· sh· W3126499918 on OpenAlexaboutno aff
Antonia Pauk

Bibliographic record

Venuenot available
Typedissertation
Languagesh
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMammographyMedical physicsDigital mammographyProtocol (science)Quality (philosophy)Image qualityEuropean commissionMedicineMedical physicistComputer scienceBreast cancerArtificial intelligencePhysicsEuropean unionBusinessCancerPathologyImage (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The topic of this paper is the comparison of quality control protocols of mammography devices in the Republic of Croatia with protocols in other countries. Mammography is the most reliable method for early detection of breast cancer aimed at providing quality mammograms with the best possible diagnostic information with the lowest possible radiation dose to patients. It is necessary to control the quality of the device since the image quality and acceptable radiation dose depend on several parameters such as breast size and density, X-ray source characteristics (alignment of X-ray field/image receptor, tube output, reproducibility and accuracy), automatic control exposure (AEC), compression, receptor efficiency, film processing, image reading and display conditions, and repeated image analysis. The correctness of mammography devices in Croatia is controlled daily, monthly and annually by precisely prescribed protocols using appropriate phantoms. Quality control is performed by radiological technologists and medical physicists, but also by device manufacturers' service technicians and inspectors as needed. The aim of this paper is to compare protocols that control the quality of mammography devices in other countries based on the Canadian and European protocols. A literature search will establish guidelines for the implementation of quality control in mammography, which are available worldwide from health care providers, but also from scientific and professional associations. The Croatian and Canadian protocols and the protocol of the European Commission focused on conventional and digital mammography will be described. Finally, the aim is to show difference between protocols, to show the advantages and disadvantages, and to conclude which would be the most ideal in terms of comprehensiveness, practicality and cost-effectiveness.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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 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
Published2020
Admission routes1
Has abstractyes

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