HectoMAP: The Complete Redshift Survey (Data Release 2)
Bibliographic record
Abstract
Abstract HectoMAP is a dense redshift survey of 95,403 galaxies based primarily on MMT spectroscopy with a median redshift z = 0.345. The survey covers 54.64 deg2 in a 1.°5 wide strip across the northern sky centered at a decl. of 43.°25. We report the redshift, the spectral indicator D n 4000, and the stellar mass. The red-selected survey is 81% complete for 55,962 galaxies with (g − r) > 1 and r < 20.5; it is 72% complete for 32,908 galaxies with (g − r) > 1, (r − i) > 0.5 and 20.5 < r < 21.3. Comparison of the survey basis SDSS photometry with the HSC-SSP photometry demonstrates that HectoMAP provides complete magnitude-limited surveys based on either photometric system. We update the comparison between the HSC-SSP photometric redshifts with HectoMAP spectroscopic redshifts; the comparison demonstrates that the HSC-SSP photometric redshifts have improved between the second and third data releases. HectoMAP is a foundation for examining the quiescent galaxy population (63% of the survey), clusters of galaxies, and the cosmic web. HectoMAP is completely covered by the HSC-SSP survey, thus enabling a variety of strong- and weak-lensing investigations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.018 |
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".