Record Commission [of Nova Scotia]. The second report of Thomas B. Akins.
Bibliographic record
Abstract
The second report of Thomas B. Akins, appointed by his excellency the lieutenant"" governor, on the 20th clay of May, 1857, to be commissioner of public records under a resolution passed in the house of assembly on the 3d s£f day of April in the same year, as follows : -" That his excellency be respectfully requested to c•* c the ancient records and documents illustrative of the history and progross of " society in this province to be examined, preserved and arranged, either for refer- " ence or publication, as the legislature may hereafter determine, and that the " house will provide for the same."To his excellency the right honorable the Earl of Mulgrave, lieutenant-governor and commander in chief in and over her majesty's province of Nova Scotia and its dependencies, §-c, $*c,, $*c.May it please your excellency, -Soon after the prorogation of the legislature in TVlay last, I resumed my labors in accordance with the resolution of the assembly on the record commission, passed on 22nd day of April last.A large mass of papers s: >j:arated anij assorted in boxes last year, for future exami- nation, were taken up.T lion ofniid selections from-these papers, with the documents appertaining to b - 1 Mature contained-in the closets of the speaker's room and the small council chain i ai tit# correspondence from 1800 to 1834, constituted the chief part of the work of the past year.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.191 | 0.112 |
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".