522 research outputs found

    Goodhart's law and machine learning: a structural perspective

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    We develop a simple structural model to illustrate how penalized regressions generate Goodhart bias when training data are clean but covariates are manipulated at known cost by future agents. With quadratic (extremely steep) manipulation costs, bias is proportional to Ridge (Lasso) penalization. If costs depend on absolute or percentage manipulation, the following algorithm yields manipulation-proof prediction: Within training data, evaluate candidate coefficients at their respective incentive-compatible manipulation configuration. We derive analytical coefficient adjustments: slopes (intercept) shift downward if costs depend on percentage (absolute) manipulation. Statisticians ignoring manipulation costs select socially suboptimal penalization. Model averaging reduces these manipulation costs

    Measuring recovery capital for people recovering from alcohol and drug addiction:A systematic review

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    Background: Recovery capital (RC) theory provides a biopsychosocial framework for identifying and measuring strengths and barriers that can be targeted to support recovery from alcohol and drug addiction. This systematic review analyzed and synthesized all quantitative approaches that have been used to measured recovery capital RC in the recent literaturesince 2016.Method: Systematic database searches were conducted in three databases to identifyThe reviewed studies were published from 2016 to 2023, . Eligible studiesand explicitly stated they measured RC recovery capital in participants recovering from alcohol and/or drug addiction. Studies focusing on other forms of addiction were excluded.Results: Sixty-nine studies met the inclusion criteria. Forty-six studies (66.7%) used one of the ten identified RC recovery capital questionnaires, and twenty-five studies (36.2%) used a measurement approach other than one of the ten RC recovery capital questionnaires. The ten RC recovery capital questionnaires are primarily developed for adult populations across clinical and community recovery settings, and between them measuredwere identified to measure altogether 41 separate RC recovery capital constructs. They, and are generally considered valid and reliable measures of RCrecovery capital. Nevertheless, a strong evidence base on the psychometric properties across diverse populations and settings is still needs to be established for all RC these questionnaires. Conclusion: The development of RC recovery capital questionnaires has been a significant advance in the addiction recovery field, in alignment with the modern emerging recovery-oriented approach to addiction recovery care. Additionally, the non-RC recovery capital questionnaire-based approaches to RC recovery capital measurement have an important place in the field. They could be used alongside RC recovery capital questionnaires to test RC theory, and in contexts where the application of the RC questionnaires is not feasible, such as analyses of data from online recovery forums

    Charge-coupled devices detectors with high quantum efficiency at UV wavelengths

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    We report on multilayer high efficiency antireflection coating (ARC) design and development for use at UV wavelengths on CCDs and other Si-based detectors. We have previously demonstrated a set of single-layer coatings, which achieve >50% quantum efficiency (QE) in four bands from 130 to 300 nm. We now present multilayer coating designs that significantly outperform our previous work between 195 and 215 nm. Using up to 11 layers, we present several model designs to reach QE above 80%. We also demonstrate the successful performance of 5 and 11 layer ARCs on silicon and fused silica substrates. Finally, we present a five-layer coating deposited onto a thinned, delta-doped CCD and demonstrate external QE greater than 60% between 202 and 208 nm, with a peak of 67.6% at 206 nm

    KL Estimation of the Power Spectrum Parameters from the Angular Distribution of Galaxies in Early SDSS Data

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    We present measurements of parameters of the 3-dimensional power spectrum of galaxy clustering from 222 square degrees of early imaging data in the Sloan Digital Sky Survey. The projected galaxy distribution on the sky is expanded over a set of Karhunen-Loeve eigenfunctions, which optimize the signal-to-noise ratio in our analysis. A maximum likelihood analysis is used to estimate parameters that set the shape and amplitude of the 3-dimensional power spectrum. Our best estimates are Gamma=0.188 +/- 0.04 and sigma_8L = 0.915 +/- 0.06 (statistical errors only), for a flat Universe with a cosmological constant. We demonstrate that our measurements contain signal from scales at or beyond the peak of the 3D power spectrum. We discuss how the results scale with systematic uncertainties, like the radial selection function. We find that the central values satisfy the analytically estimated scaling relation. We have also explored the effects of evolutionary corrections, various truncations of the KL basis, seeing, sample size and limiting magnitude. We find that the impact of most of these uncertainties stay within the 2-sigma uncertainties of our fiducial result.Comment: Fig 1 postscript problem correcte

    The Angular Correlation Function of Galaxies from Early SDSS Data

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    The Sloan Digital Sky Survey is one of the first multicolor photometric and spectroscopic surveys designed to measure the statistical properties of galaxies within the local Universe. In this Letter we present some of the initial results on the angular 2-point correlation function measured from the early SDSS galaxy data. The form of the correlation function, over the magnitude interval 18<r*<22, is shown to be consistent with results from existing wide-field, photographic-based surveys and narrower CCD galaxy surveys. On scales between 1 arcminute and 1 degree the correlation function is well described by a power-law with an exponent of ~ -0.7. The amplitude of the correlation function, within this angular interval, decreases with fainter magnitudes in good agreement with analyses from existing galaxy surveys. There is a characteristic break in the correlation function on scales of approximately 1-2 degrees. On small scales, < 1', the SDSS correlation function does not appear to be consistent with the power-law form fitted to the 1'< theta <0.5 deg data. With a data set that is less than 2% of the full SDSS survey area, we have obtained high precision measurements of the power-law angular correlation function on angular scales 1' < theta < 1 deg, which are robust to systematic uncertainties. Because of the limited area and the highly correlated nature of the error covariance matrix, these initial results do not yet provide a definitive characterization of departures from the power-law form at smaller and larger angles. In the near future, however, the area of the SDSS imaging survey will be sufficient to allow detailed analysis of the small and large scale regimes, measurements of higher-order correlations, and studies of angular clustering as a function of redshift and galaxy type

    Galaxy Clustering in Early SDSS Redshift Data

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    We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5,700 km/s < cz < 39,000 km/s, distributed in several long but narrow (2.5-5 degree) segments, covering 690 square degrees. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 Mpc/h. The two-dimensional correlation function \xi(r_p,\pi) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, \xi(r)=(r/6.1+/-0.2 Mpc/h)^{-1.75+/-0.03}, for 0.1 Mpc/h < r < 16 Mpc/h. The galaxy pairwise velocity dispersion is \sigma_{12} ~ 600+/-100 km/s for projected separations 0.15 Mpc/h < r_p < 5 Mpc/h. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r < 10 Mpc/h: subsamples with absolute magnitude ranges centered on M_*-1.5, M_*, and M_*+1.5 have real-space correlation functions that are parallel power laws of slope ~ -1.8 with correlation lengths of approximately 7.4 Mpc/h, 6.3 Mpc/h, and 4.7 Mpc/h, respectively.Comment: 51 pages, 18 figures. Replaced to match accepted ApJ versio
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