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Record W6929867566 · doi:10.5066/p92jgacb

Status and Trends of North American Bats Summer Occupancy Analysis 2010-2019 Data Release

2022· dataset· en· W6929867566 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2022
Typedataset
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOccupancyGrid cellOccupancy grid mappingGeospatial analysisGridSpatial ecologyHabitatPopulation

Abstract

fetched live from OpenAlex

This data release contains the results from the North American Bat Monitoring Program's report titled 'Status and Trends of North American Bats Summer Occupancy Analysis 2010-2019'. Specifically, these data include tabular data and geospatial data for the species-specific results related to the status and trends of 12 bat species at multiple spatial scales including: 10 km x 10 km grid cells, state/province/territories, and range-wide across the geographic extent of monitoring data for each species (i.e., across 'modeled species ranges'). They were produced using an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to assess the summer (May 1-Aug 31) population status and trends of North American bat species across their modeled ranges at multiple spatial scales. An occupancy model was estimated for each species while accounting for biases from false positives (i.e., misclassification error) and false negatives (i.e., detectability). Then, using the estimated relationships between grid cell occupancy probabilities for each species with ecological and spatiotemporal predictors, maps of species occupancy probabilities were produced for each year of sampling, for each NABat grid cell in each species' 'modeled range'. Finally, status and trends indicators across larger spatial extents (e.g. range-wide, state/territory/province) were derived based on the grid cell level occupancy probabilities over time. A tabular file is included for each species detailing the occupancy probability predictions of each 10 km x 10 km grid cell in each modeled species range, with predictions (means, and the 95% credible intervals) for every year of monitoring data. Next, a geospatial layer is provided that contains the merged NABat Master Sampling Grid (i.e., the union of sampling frames for Continental United States and Canada + Alaska ) with a unique grid cell identifier ('grts') to allow joining the tabular estimates to the NABat grid cells. This geospatial layer can assist grid cell level visualizations of species occupancy probability distributions over time, and also includes grid cell level occupancy covariates used in these analyses. Additional results include a tabular file that contains the range-wide and regional estimates of species status and trend including: the mean grid cell occupancy probability across each larger spatial extent (e.g., modeled species range, states/territories/provinces) for every species and year of species monitoring data analyzed. Two additional trend indicators for species occupancy (the average annual change rate, and the total change rate) were included in the same file, across several time frames including 3 years of change (and 4 years of monitoring data from 2016 - 2019) and where possible, also over 7 years of change (8 years of monitoring data from 2012 - 2019) and 9 years of change (10 years of monitoring data from 2010 - 2019).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0260.019

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 head0.046
GPT teacher head0.274
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2022
Admission routes1
Has abstractyes

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