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Record W42706792 · doi:10.1385/1-59259-892-7:059

Role of TGF-β and IGF in Tumor Progression and Bone Metastases

2005· book-chapter· en· W42706792 on OpenAlexaff
Erin D. Giles, Gurmit Singh

Bibliographic record

VenueHumana Press eBooks · 2005
Typebook-chapter
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsProstate cancerBreast cancerMedicineTumor microenvironmentCancer researchDiseaseTransforming growth factorBone metastasisOncologyPathologyCancerBiologyInternal medicineTumor cells

Abstract

fetched live from OpenAlex

Metastatic disease contributes to a large proportion of cancer-related deaths, and bone is among the most common sites for metastases for tumors originating in the breast and prostate. The propensity for these cancers to form bone metastases is not completely understood; however, it undoubtedly involves a number of unique characteristics of both the tumor cells and the bone microenvironment. Such an explanation was proposed more than a decade ago with Paget’s “seed and soil” hypothesis, which suggested that meta-static cells are dispersed throughout the body, yet they will only survive and grow upon reaching tissues that are optimal for their growth (reviewed in ref. 1 ). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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 designBench or experimental
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
Published2005
Admission routes1
Has abstractyes

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