New Perspectives and Methods in Loss Reserving Using Generalized Linear Models
Bibliographic record
Abstract
We sought to examine placentas enriched for trophoblast inclusions (TIs) in order to characterize, quantify, and examine the interrelations between subtypes of TIs to better understand their underlying biology. We examined a cohort of 600 placentas from deliveries between 20<sup>0</sup> and 43<sup>0</sup> weeks of gestation. Forty-five percent of the placentas had at least one TI in the two slides examined. Four percent of the placentas had 10 or more TIs and two placentas had more than 70 TIs. Four distinct TI subtypes were observed: inclusionoids (early forming inclusions), inclusions, calcified inclusions, and calcified bodies. We suggest this reflects a developmental trajectory of TI maturation, the timing of which might be useful when comparing TI expression to clinical outcomes.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".