Bibliographic record
Abstract
Objective To investigate the features and value of different kinds of imaging methods in lungcancer with bone metastasis.Methods Imaging findings of plain fimls,CT and MRI in 68 cases of lung cancer with bone metastasis were retrospectively analyzed.The patients aged from 35 to 78 years old and were divided into two groups according to their age.The lesions' location and imaging changes were summarized.Results The patients aged below 49 years were 12 cases(18%) and above 50 years were 56 cases(82%).Multiple bone metastasis were found in 42 cases(62%),single bone metastasis in 18 cases(38%).The lesions appeared irregular osteolytic bone destruction and soft tissue mass(79.4%),sightly expansive honeycomb bone destruction(14.7%),patchy osteoblastic change(4.4%)and patchy mixed osteolytic and osteoblastic change(1.5%).Conclusion Bone metastasis from lung cancer were multiple and mainly located in axis bones.The rate of finding lesions was high in CT and MRI examination,and MRI could find small lesions and MRI was used to exam extremities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".