Bibliographic record
Abstract
I'Ih' Nucinl I'i'iiiro of this liidliiric cily.('uiliiiiiiijiliiiicly Fiiliiiilcil 1.11 DulTcrm TiTmeo. it iilfuriN nirtaMi1ii<'rii vi (-vv!i ot llif iii)bU> St Ijittrriirt' It is iin iilnil itcippinn I"""' '"' I'lllict tlif Iniirivl iir till' l>i)>iini-v iiiiiii Mo^iilr" tlir Ki^'Mic mill liii«l l nf IJiii'lii'i-, Kolf, liiijloniiu mill i.'ji«ily-n?inli('il tisliiiin iifc iiv:iiliilik-In visitor*.I'.xciirsioiiK lui III' iiiiiili'' lu MDiiliiiurtiiry Kiilln, ^ti'.Aiiiic ilc llciiit|iri.S rli^In iniilpT, 111!' t'imlenii I'VimluiiiiL' if llu' licii'liiiiiiPloni of a siilciiilicl ii'inirr iimrl spiiwon.THE PLACE VICER.MONTREAL A rliiiniiii>)i liiii-.'lthill iiiiihcs nil iilcal cviilrc Tor lliusi.' v/\\i> liri'ti't igiiii^l iiixl yi'l vvinli to lii' within eaay rcuvli of tli(> liusiiii.-s.i iinil slmpimig diairiclii.Closi' to Ihi-ilorks mid Ihe old liiKliirir occtiiiio.mill > jiupiilnr soniil rendcii-voiiii.riic Plucc VluM (isliidt nd)nl"« I'lucc Viun Sliilli.ii.liikJ ii 1 It iiilli-i ri.iii.Ulncl«orSIalion)I»fl|iMiilf'l<i'i Itit Kuruuraii ptoii.A Ai loree.olmoM.oj half of Europe.Ihe beautiful MaSnilicenl proinnce of Quebec has dtikc for ihe lourist.the Ptavincc irovelkr nnd il) own pcopk o wcallti of atiraelioti.The giandrsi rivir ot North Anicricu.the noble Si.Lowtecce.fed by mighly tributaries, threads it fot a Ihouiand mile*.Thus there orr tema/koble oppQtt unities for fishine.hunting nnd nil outdoor Dctiviti"On the lolie-shores from -nd to end of ihi province ore summer resorts innumerable, with accom- mo
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.003 |
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".