North American Bird Banding Program Dataset 1960-2020 retrieved 2020-06-26
Bibliographic record
Abstract
Note: this version has been superseded by: Celis-Murillo, A., Malorodova, M., and Nakash, E., 2021, North American Bird Banding Program Dataset 1960-2021 retrieved 2021-07-25: U.S. Geological Survey data release, https://doi.org/10.5066/P91YDWYS. The North American Bird Banding Program is directed in the United States by the U.S. Geological Survey (USGS) Bird Banding Laboratory (BBL), Eastern Ecological Science Center at the Patuxent Research Refuge (EESC) and in Canada by the Bird Banding Office (BBO), Environment and Climate Change Canada (ECCC). The respective banding offices have similar functions and policies and use the same bands, reporting forms and data formats. Data contributors are US and Canadian bird banding permit holders: federal, state, tribal, local government, non-government agencies, business, university and avocational biologists. Bird banders capture wild birds and mark them with a metal leg band with a unique 9-digit number. Extra markers may be added. Attributes of a bird such as age, sex, condition, molt and morphometrics may be taken before the bird is released. This long-term dataset is made up of over 77 million bird banding records with over 1,000 species, and over 5 million encounter records with nearly 800 species. Federal bands are used on species included in the Migratory Bird Treaty Act (MBTA). Banding, encounter and recapture records are available for years 1960 to present. The data is curated at BBL on a daily basis, therefore each yearly version may differ from previous releases. The BBL produces one data release annually, beginning in 2020. Each yearly release is available for request. Data quality is established by contributors submitting their data. Incoming data must pass automatic validation rules to meet quality standards, and in some cases additional validation is conducted by staff at BBL and BBO. It is imperative to understand the codes used by the BBL and BBO. In early days of storage space restrictions for electronic data, an efficient system of codes was developed. Some examples include: bird status code, coordinate precision, inexact date, minimum age at encounter. BBL terminology is important as well: an encounter refers to a sighting or direct encounter with a banded or auxiliary-marked bird by any person; recapture denotes a banded bird recaptured during banding operations; recovery refers a harvested gamebird. Please cite as: Celis-Murillo A, M Malorodova, E Nakash. 2020. North American Bird Banding Dataset 1960-2020 retrieved 2020-06-26. U.S. Geological Survey, Eastern Ecological Science Center at the Patuxent Research Refuge.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.068 |
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".