Arnaud Badets, Yannick Blandin, David L. Wright et al. · Research Quarterly for Exercise and Sport · 2006
The purpose of this experiment was to determine whether a faded knowledge of results (KR) frequency during observation of a model's performance enhanced error detection capabilities. During the observation phase, participants observed a model performing a timing task and received KR about the model's performance on each trial or on one of two trials. Delayed retention and transfer tests were used to assess the observer's ability to detect error in the model's performance and in the participant's performance while physically practicing the task. Results indicated a beneficial effect of a reduced KR frequency for performance stability and the ability to detect errors in both the model and the participant's own performance. The results suggest that aspects of the processing mechanism(s) developed in observational learning and related to KR are probably similar to those developed through physical practice.
Cited by 33
Baer, James, Chesley, Steven R., Milani, Andrea · ResearchOnline at James Cook University (James Cook University) · 2011
Cited by 0
Marcus A. Thomas · ArXiv.org · 2025
We argue that progress toward AGI is theory limited rather than data or scale limited. Building on the critical rationalism of Popper and Deutsch, we challenge the Platonic Representation Hypothesis. Observationally equivalent worlds can diverge under interventions, so observational adequacy alone cannot guarantee interventional competence. We begin by laying foundations, definitions of knowledge, learning, intelligence, counterfactual competence and AGI, and then analyze the limits of observational learning that motivate an error centric shift. We recast the problem as three questions about how explicit and implicit errors evolve under an agent's actions, which errors are unreachable within a fixed hypothesis space, and how conjecture and criticism expand that space. From these questions we propose Causal Mechanics, a mechanisms first program in which hypothesis space change is a first class operation and probabilistic structure is used when useful rather than presumed. We advance structural principles that make error discovery and correction tractable, including a differential Locality and Autonomy Principle for modular interventions, a gauge invariant form of Independent Causal Mechanisms for separability, and the Compositional Autonomy Principle for analogy preservation, together with actionable diagnostics. The aim is a scaffold for systems that can convert unreachable errors into reachable ones and correct them.
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Raquel Pelayo · Open Repository of the University of Porto (University of Porto) · 2014
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Taoyun ZHOU, Baowang LIAN, Dongdong YANG et al. · SHILAP Revista de lepidopterología · 2019
Aiming at the problem of not enough influencing factors were considered in traditional methods,a much more realistic stochastic model was built.In which error corrections were introduced into the geometry-based function model,an improved least squares variance component estimation (LS-VCE) algorithm with space-for-time was used to solve the model,two sets of real GPS data were collected to evaluate the performance of the model,and with which the carrier phase integer ambiguity was solved.The experimental results show that the proposed methods are superior to the traditional methods in terms of model accuracy,model solution complexity and integer ambiguity resolution.
Cited by 1Open access
Charles B. Black, David L. Wright · Research Quarterly for Exercise and Sport · 2000
Two experiments are reported that examined the usefulness of observational learning for acquiring both error detection and movement production capabilities. In both experiments, individuals were assigned to a no-practice, physical-practice, or observational practice condition. Those assigned to a physical-practice condition acted as models for those assigned as observers. In both experiments, models were administered a random practice of three serial key-press tasks that had the same spatial pattern and same relative timing requirement but differed in the overall time goal. During the retention test, individuals provided estimates of their overall time after each trial. Data from these experiments revealed that error detection and overall time specification were similar following observation and physical practice. However, data from Experiment 2 indicated that physical practice offered an advantage beyond that afforded via observation, with regard to acquiring the appropriate relative time pattern. These data are discussed with respect to the role of observation for learning movement recognition and production processes.
Cited by 69
Gerardo Garcés Martín, José M. Castellano, Enrique Guerado et al. · 1990
Cited by 0
Monika Petelczyc, Jan Gierałtowski, Barbara Żogała-Siudem et al. · Heliyon · 2020
An observational error of heart rate variability (HRV) may arise from many factors, such as a limited sampling frequency, QRS complexes detection process, preprocessing procedures and others. In our study, we focused on the first two origins of measurement error. We introduced a model of observational error and suggested universal descriptors for the assessment of its resultant magnitude in terms of time, frequency as well as nonlinear parameters. For this purpose, we applied Monte Carlo simulations which showed that the most sensitive to observational error are: pNN50 (the proportion of pairs of successive RR intervals that differ by more than 50 ms) and markers obtained from frequency analysis. On the other hand, the most resistant are other time domain parameters as well as the short and long-term slopes of Detrended Fluctuation Analysis (DFA). We postulate that the observational error should be considered in population studies, when different recorders are used in the research centres. Additionally, in the case of patients with similar etiology of disease but with different heart rhythms abnormalities the scatter of HRV parameters will also be observed due to the subject's the time series variability.
Cited by 18Open access
Alison Fowler · Tellus A Dynamic Meteorology and Oceanography · 2019
Numerical weather prediction (NWP) models are moving towards km-scale (and smaller) resolutions in order to forecast high-impact weather. As the resolution of NWP models increase the need for high-resolution observations to constrain these models also increases. A major hurdle to the assimilation of dense observations in NWP is the presence of non-negligible observation error correlations (OECs). Despite the difficulty in estimating these error correlations, progress is being made, with centres around the world now explicitly accounting for OECs in a variety of observation types. This paper explores how to make efficient use of this potentially dramatic increase in the amount of data available for assimilation. In an idealised framework it is illustrated that as the length-scales of the OECs increase the scales that the analysis is most sensitive to the observations become smaller. This implies that a denser network of observations is more beneficial with increasing OEC length-scales. However, the computational and storage burden associated with such a dense network may not be feasible. To reduce the amount of data, a compression technique based on retaining the maximum information content of the observations can be used. When the OEC length-scales are large (in comparison to the prior error correlations), the data compression will select observations of the smaller scales for assimilation whilst throwing out the larger scale information. In this case it is shown that there is a discrepancy between the observations with the maximum information and those that minimise the analysis error variances. Experiments are performed using the Ensemble Kalman Filter and the Lorenz-1996 model, comparing different forms of data reduction. It is found that as the OEC length-scales increase the assimilation becomes more sensitive to the choice of data reduction technique.
Cited by 18Open access
WAN AZHAR WAN AHMAD · Zenodo (CERN European Organization for Nuclear Research) · 2026
While the current cryptographic landscape relies on ’Certified Randomness’ as an absolute safeguard, this paper argues that such entropy is merely an illusion born of dimensional blindness. We present Structural Unification Theory (SUT), which moves beyond the probabilistic models of the last decade to reveal a deterministic universe. By applying the Master Identity i = c +γ, we demonstrate that so-called ’Quantum Noise’ is the measurable high frequency vibration of a 26-dimensional rigid manifold. Anchored by a −1/12 substrate, this manifold suggests that what we perceive as ’randomity’ is actually a high-order geometric signal that is fully predictable within a unified framework.
Cited by 0Open access
Wanling Wu · 2004
There is always error on original observational data of the differential-resistance meter, the characteristic form of error is determined by the special structure and principle of the meter.This article enumerates several familiars styles of errors from application, it analyzes the causes of error and disposal as well.
Cited by 0
WAN AZHAR WAN AHMAD · Zenodo (CERN European Organization for Nuclear Research) · 2026
While the current cryptographic landscape relies on ’Certified Randomness’ as an absolute safeguard, this paper argues that such entropy is merely an illusion born of dimensional blindness. We present Structural Unification Theory (SUT), which moves beyond the probabilistic models of the last decade to reveal a deterministic universe. By applying the Master Identity i = c +γ, we demonstrate that so-called ’Quantum Noise’ is the measurable high frequency vibration of a 26-dimensional rigid manifold. Anchored by a −1/12 substrate, this manifold suggests that what we perceive as ’randomity’ is actually a high-order geometric signal that is fully predictable within a unified framework.
Cited by 0Open access
Janjić, Tijana, Albertella, Alberta, Skachko, Sergey et al. · Publication Server of the Catholic University Eichstätt-Ingolstadt (Catholic University of Eichstätt-Ingolstadt) · 2009
Cited by 0
Janjic Pfander, Tijana, Albertella, A., Skachko, Sergey et al. · Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut) · 2009
Cited by 0Open access
Francesco Feri, Miguel A. Meléndez-Jímenez, Giovanni Ponti et al. · Games and Economic Behavior · 2010
Cited by 36
Sarah C. Kramer (6407927), Sen Pei (736312), Jeffrey Shaman (252813) · Figshare · 2020
<p>Ratios are plotted separately for the (A) metapopulation and (B) isolated models. The black line shows the median ratio over all countries, (sub)types, seasons, and runs; 50% and 95% credible intervals are shaded in dark and light gray, respectively. The y-axis is plotted on a log scale.</p> <p>(SVG)</p>
Cited by 0Open access
Francesco Ceccarini, Umberto Castiello · Psychonomic Bulletin & Review · 2018
Cited by 5Open access
Irwin Roman · Geophysics · 1946
Abstract By using a four-step oscillating method of observation, four values are obtained for the increment in the measured value between consecutive stations. If the drift or 'zero creep' of the instrument is regular, even when large, or not linear, this furnishes a means of improving the reliability of the readings and permits the detection of erratic readings. In areal surveys, a primary net of values may be established by this oscillating method and this net used as a base into which to adjust chains of observations. Intermediate values may sometimes be desirable, such values being adjusted into the primary net by the oscillating method. An example shows the application of the method to a gravimetric survey.
Cited by 9
Choi, J. · Leiden Repository (Leiden University) · 2023
<p>This thesis addresses potential threats to the validity of observational epidemiological studies. Examples of these potential sources of bias are confounding, missing data, selection bias, and measurement error. Although various methods have been developed to mitigate these biases, it is often unclear which methods can be used in which empirical settings. It is also common that issues discussed in methodological studies are overlooked in clinical research. Thus, we investigated problems of<br>missing data, selection bias, and measurement error occurring in several specific observational settings and discuss how to optimally handle them.<br></p>
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G. Candille, Olivier Talagrand · Quarterly Journal of the Royal Meteorological Society · 2008
Abstract Ensemble prediction systems (EPSs) are usually validated under the assumption that the verifying observations are exact. In this paper, two methods are considered for taking observation errors into account. In the ‘perturbed‐ensemble’ method, which has already been studied by other authors, the predicted ensemble elements are randomly perturbed in a way that is consistent with the assumed observation error. In the ‘observational‐probability’ method, which is new, a verifying observation is considered as defining, together with the assumed associated error, a probability distribution. All standard scores for evaluation of EPSs (reliability diagram, Brier score, ranked probability score (RPS), continuous RPS (CRPS), relative‐operating‐characteristics (ROC) curve area), with the exception of the rank histogram, remain defined in this second method. In particular, the classical reliability–resolution decomposition of the Brier score, and of its extension to the RPS and CRPS, remain defined. Numerical simulations, partially supported by theoretical considerations, show that, with respect to the case when observation errors are ignored, the perturbed‐ensemble method improves reliability, as well as the ROC score, while it has no significant impact on resolution, as measured by the Brier score. The observational‐probability method, on the other hand, degrades reliability and the ROC score, but improves resolution. With respect to the ‘real’ performance of the system (i.e. the one that would be diagnosed if no error were present), reliability is unchanged in the perturbed‐ensemble method, while resolution and the ROC score are degraded. The observational‐probability method degrades reliability and the ROC score. As for resolution, an optimum value of the observational error is found, below which resolution is improved. Diagnostics performed on the operational EPS of the Canadian Meteorological Centre confirm the results of the simulations as to the consequences of ignoring observation errors, or on the contrary of taking them into account through either of the two methods. The significance of those various results is discussed. This article replaces a previously published version ( Q. J. R. Meteorol. Soc. 134 (631): 509–521, DOI: 10.1002/qj.221). Copyright © 2008 Royal Meteorological Society
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