Bibliographic record
Abstract
1 Windsor's factory district in 1911 / 5 2 The Detroit River in 1900 / 19 3 The Ford Motor Company of Canada, established in Walkerville in 1904 / 21 4 A map of Windsor and the rest of the border cities in 1913 / 23 5 A bird's-eye view of downtown Windsor -and the bustling Detroit River waterfront -in 1914 / 28 6 A view of the ferry from Ouellette Street in 1913 / 33 7 Residents of Windsor distribute Camel cigarettes to American soldiers as they pass through in 1918 / 41 8 American doughboys passing through Windsor in 1918 fill out postcards from residents / 43 9 Looking west along Pitt Street -one block south of the Detroit Riverin 1914 / 46 10 The Peabody factory in 1913 / 48 11 A ferry crossing the Detroit River and international boundary in 1905 / 57 12 Residents of Windsor greet thousands of American soldiers as they pass through in 1918 en route to the front / 67 13 St.Stephen and Calais, still booming places in 1889 / 74 14 St. Stephen's Water Street in 1906 / 80 15 Horse racing in Calais in 1912, drawing spectators from both sides of the international boundary / 84 16 The 55th Battalion departing from Charlotte County for the front in 1915 / 88 17 The 55th Battalion entraining at the St. Stephen railway station in May 1915 / 93 18 The first bridge connecting the downtown areas of St. Stephen and Calais, completed in 1827 / 102 19 The infamous St. Leonard Hotel just before the First World War / 114 20 White Rock, which grew rapidly during the first decades of the twentieth century / 117 21 White Rock's pier, built in 1914 with federal funding / 124 22 Looking south along the Great Northern Railway track, which separated White Rock from its pristine beaches / 125 23 The White Rock townsite plan in 1912 / 129
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.797 | 0.614 |
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".