Source counts at 15 microns from the AKARI NEP survey
Bibliographic record
Abstract
We present galaxy counts at 15 microns using the Japanese AKARI satelitte's NEP-deep and NEP-wide legacy surveys at the north ecliptic pole. The total number of sources detected are approximately 6700 and 10 700 down to limiting fluxes of 117 and 250 microJy (5 sigma) for the NEP-deep and NEP-wide survey respectively. We construct the Euclidean normalized differential source counts for both data sets (assuming 80 percent completeness levels of 200 and 270 microJy respectively) to produce the widest and deepest contiguous survey at 15 microns to date covering the entire flux range from the deepest to shallowest surveys made with the infrared space observatory (ISO) over areas sufficiently significant to overcome cosmic variance, detecting six times as many sources as the largest survey carried out with ISO. We compare the results from AKARI with the previous surveys with ISO at the same wavelength and the Spitzer observations at 16 microns using the peek-up camera on its IRS instrument. The AKARI source counts are consistent with other results to date reproducing the steep evolutionary rise at fluxes less than a milliJansky and super-Euclidean slopes. We find the the AKARI source counts show a slight excess at fluxes fainter than 200 microJanskys which is not predicted by previous source count models at 15 microns. However, we caution that at this level we may be suffering from the effects of source confusion in our data. At brighter fluxes greater than a milliJansky, the NEP-wide survey source counts agree with the Northern ISO-ELAIS field results, resolving the discrepancy of the bright end calibration in the ISO 15 micron source counts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".