The LOFAR Two-metre Sky Survey III. First data release: Optical/infrared identifications and value-added catalogue
Bibliographic record
Abstract
The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120-168 MHz survey of the northern sky with diverse and ambitious science goals.Many of the scientific objectives of LoTSS rely upon, or are enhanced by, the association or separation of the sometimes incorrectly catalogued radio components into distinct radio sources and the identification and characterisation of the optical counterparts to these sources.We present the source associations and optical and/or IR identifications for sources in the first data release, which are made using a combination of statistical techniques and visual association and identification.We document in detail the colour-and magnitudedependent likelihood ratio method used for statistical identification as well as the Zooniverse project, called LOFAR Galaxy Zoo, used for visual classification.We describe the process used to select which of these two different methods is most appropriate for each LoTSS source.The final LoTSS-DR1-IDs value-added catalogue presented contains 318,520 radio sources, of which 231,716 (73%) have optical and/or IR identifications in Pan-STARRS and WISE.The valueadded catalogue is available on-line at https://lofar-surveys.org/, as part of this data release.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.060 |
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".