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Record W7023475450

Ontario as a home for the British tenant farmer who desires to become his own landlord.

2014· article· en· W7023475450 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsShoreSquare (algebra)Boundary (topology)BaySwampFence (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Ontario embraces an area of nearly two hundred thousand square miles, about eighty thousand more than the United Kingdom.It extends from east to west nearly eleven hundred mites, and from north to south seven hundred miles.Its southern border, Essex County, on the shores of Lake Erie, is traversed by the 42nd parallel, and its northern, at James Bay (forming the southern extremity of Hudson's Bay) by the 52nd, so that it lies within the same degrees of latitude as Michigan, New York, and the New England States, as well as the greater portion of the most fertile countries in Europe.The international boundary line, dividing Canada from the United States, which runs through the River St. Lawrence and the great chain of lakes, Ontario, Erie, Huron and Superior, forms the southern and south-western boundary of the Province ; on the west lies the Province of Manitoba ; on the north the District of Keewatin and James' B*y, and nwith-easterly the Ottawa Ri<er divides it from Quebec, the latter Province forming the eastern boundary. WATER SUPPLY.It is bountifully supplied with water throughout its whole extent ; there are patches of swamp land in some districts, but they are usually of small dimensions, and though little fitted for the purposes of agriculture, are exceedingly valuable to a neighborhood on account of the durability of their timber, which is specially adapted for the making of shingles, posts, fence rails, paving-blocks, etc., etc.But nowhere is there an arid district, or one iu which an abundant water-supply cat i not be readily procured, both for man and beast.Besides innumerable lakes, rivers, creeks- and streamlets, springs abound in many localities, and everywhere under the soil pure, wholesome uater can be "struck" at distances varying from fourteen to forty feet, so that sinking a well, which is frequently a necessity for an isolated household, is very seldom attended with very much trouble or great expense. NATURAL WEALTH.Ontario's vast wealth of timber is still on j of its most valuable heritages, capable of furnishing an abundant supply, both for home consumption and for every probable demand that commerce can make upon it for genera- tions to come.The great region which is the main depository of nature's most liberal gif bs in mineral wealth is as yet only partially explored.But it is established beyond doubt that the Districts of Algoma, Nipissing, Thunder Bay and Rainy River are enormously rich in nickel, iron, silver, copper and many other minerals.In the Ottawa region, in addition to these, there have been considerable finds of gold, while the quarrying of plaster of paris or gypsum, phosphates, mica, asbestos, etc., and marble of excellent quality are profitable industries.In the southern district, near Lake Huron, are the famous oil springs from which petroleum is obtained.Further to the north are prolific salt wells, the salt obtained from which forms a large item in the commerce of that neighborhood.The salt district embraces almost the whole of the County of Huron and consider- able portions of Bruce and Lambton.Wells of natural gas have been struck in various localities between the St. Clair River and the Georgian Bay, in the Niagara district, at Mimico (near Toronto), and at other places, the gas being used both for illuminating and manufacturing purposes.There are also considerable areas of peat beds in several parts of the Province.The rivers and lakes are well supplied with fish and the forests with game.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.165
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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