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Record W7070393108

Ontario County, NY Real Property Tax Parcel Data, 2004

2018· dataset· en· W7070393108 on OpenAlexaboutno aff

Bibliographic record

VenueThe Faculty Digital Archive (New York University) · 2018
Typedataset
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsnot available
Fundersnot available
KeywordsGeocodingShapefileReal propertyMetadataProperty taxData access layerRentingProperty (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

This point shapefile layer contains features and attributes for real property tax parcels in Ontario County, NY for the year of 2004. These points represent the visual center of the parcel on a tax map; the points and associated attribute data on property ownership, assessed land value, and taxation status were extracted from local government assessment rolls. Municipalities are required by statute (Article 15) of the Real Property Tax Laws to submit Assessment Roll files after their final roll date each year. Data is submitted in various formats using a variety of media from each municipality to the Office of Real Property Services (ORPS). The data is reformatted into a standard structure and stored on the agency's Sybase database server for use in establishing equalization rates. This specific data layer was originally hosted on the NYS GIS Clearinghouse in .e00 Arcinfo interchange format and was converted into a shapefile by Michelle Thompson of NYU Data Services in June, 2018. The associated documentation was not available for this year, but attribute variables have been inferred from the Real Property Data metadata file. Points that fall outside of the county boundaries are data capture errors or geocoding errors and are marked within the attribute table. Data Services has created a simplifed codebook to assist with the interpretation and use of this data.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.058
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.049
GPT teacher head0.235
Teacher spread0.186 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Faculty Digital Archive (New York University)Same topicCalcium Carbonate Crystallization and InhibitionFrench-language works237,207