Bibliographic record
Abstract
Cambridge, Corpus Christi College 419 (pp. 38–73) [p. 38] Sunnandæges spella. Her sægð on þisum drihtnes ærendgewrite, þæt fyr cymð sumed þissa hærfesta ofer manna bearn. And hit gefealð ærest on Sceotta land, and hit þær forbærnð ealle ða fyrenfullan, þa ðe nu God gremiað mid sunnandæges weorcum and sæternesdæges ofernon. And hit þonne færð on Brytwealas and gedeð þær þæt ilce. And þonne hit færð on Angel[p.39]cyn and gedeð þær þæt ilce, þe hit dyde þam oðrum þeodum twam. Ðonne hit færð suð ofer sæ geond þæt þeodland, and hit þær forbærnð þæt mancyn, swa hit her ær dyde. Forðam, men þa leofestan, geþencan we, þæt an diacon wearð forðfered on Sceotlande, and he wæs fif wucan dead and onwoc þa eft of deaðe and spræc to mannum. And he sæde fela wundra, þe he geseah on ðære oðre weorulde. And næs ænig word, þæt ænig man on hine funde, butan [p.40] hit wære eall soð, þæt þæt he sæde. And næs syððan, þæt he æniges eorðlices metes abyrigde, ne he næfre syððan butan cyrcan ne com. And þæs diacones nama wæs Nial haten. And se diacon sæde fram þysum fyre, emne swa we rædað on sunnandæges spelle, ðæt drihten sylf gewrat iu gewrit, þæt he wolde ealle synfulle men forbærnan. BL Cotton Tiberius A.iii (83r–87r) [83r] Her sagaþ an þisan drihtnes ærendgewrite, þæt fyr cymeþ on suman hærfeste. And hit gefeallaþ ærest on Scotta land and syþþan on Angelcing and deþ þærb ælc yfel. And þonne færþ hit suþ ofer sæ on þa þeodland and forbærnþ ægþer ge mancynne man and eac cmicelne beoleofan. [83v] An diacan wæs dead nu an unmenigum geare, þæs nama wæs Nial. He wæs an Scotta ealonde, and he wæs .v. wucan dead; and he þa eft of deaþe aras þurh Cristes mihte and sprec to mannum and hiom sede fela wundra, þæs he geseah in þare oþran weorulde, þæs þe ænig mon an hine anfindan mihte butan eal soþ, þæt he sægde. And nes siþþan, þæt he ænige eorþlices metes anbergde, ne nefre siþþan he butan cirican ne com. And þæs diacones nama wæs haten Nial.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.686 | 0.481 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".