Bibliographic record
Abstract
[2] it would only give him pain--But, Thank God, it is all made plain 'now and I am hartily glad & thankful. You will never know what a relief the $50 which reached me last Tuesday from David, gave me. The taxes ($30) were due. That is to say, a fine would have been imposed if not paid within four days more and I had only $10, and was needing a cord of wood out of that. I am all right now, and was able to let Joanna have $5 more to keep her along till she gets more from Walter or until we hear from Scotland. Walter still writes encouragingly about his new business. & Joanna keeps up good courage [3] We, of the Baptist Church are in great tribulations for our new church building, which we had, with a great effort, been able to reconstruct out of the Old Presbyterian One, was on Saturday the 9th burned up. and is now a mass of ruins. I don't say burned down for the walls still stand they being remarkably strong & thick. And the rafters are still there & some or the roof but the sky can be seen through it. The flames licked the interior clean. And the poor people who sawed & hammered and dug sand & made many sacrifices to build it are now without a Church House. Mr. Fawcett preached in the Opera House yesterday to
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.825 | 0.724 |
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 source (direct Gemma or distilled Codex), 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".