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  1. Abstract

    Long-term ocean time series have proven to be the most robust approach for direct observation of climate change processes such as Ocean Acidification. The California Cooperative Oceanic Fisheries Investigations (CalCOFI) program has collected quarterly samples for seawater inorganic carbon since 1983. The longest time series is at CalCOFI line 90 station 90 from 1984–present, with a gap from 2002 to 2008. Here we present the first analysis of this 37- year time series, the oldest in the Pacific. Station 90.90 exhibits an unambiguous acidification signal in agreement with the global surface ocean (decrease in pH of −0.0015 ± 0.0001 yr−1), with a distinct seasonal cycle driven by temperature and total dissolved inorganic carbon. This provides direct evidence that the unique carbon chemistry signature (compared to other long standing time series) results in a reduced uptake rate of carbon dioxide (CO2) due to proximity to a mid-latitude eastern boundary current upwelling zone. Comparison to an independent empirical model estimate and climatology at the same location reveals regional differences not captured in the existing models.

     
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  2. Abstract Motivation

    Gene annotation is the problem of mapping proteins to their functions represented as Gene Ontology (GO) terms, typically inferred based on the primary sequences. Gene annotation is a multi-label multi-class classification problem, which has generated growing interest for its uses in the characterization of millions of proteins with unknown functions. However, there is no standard GO dataset used for benchmarking the newly developed new machine learning models within the bioinformatics community. Thus, the significance of improvements for these models remains unclear.

    Results

    The Gene Benchmarking database is the first effort to provide an easy-to-use and configurable hub for the learning and evaluation of gene annotation models. It provides easy access to pre-specified datasets and takes the non-trivial steps of preprocessing and filtering all data according to custom presets using a web interface. The GO bench web application can also be used to evaluate and display any trained model on leaderboards for annotation tasks.

    Availability and implementation

    The GO Benchmarking dataset is freely available at www.gobench.org. Code is hosted at github.com/mofradlab, with repositories for website code, core utilities and examples of usage (Supplementary Section S.7).

    Supplementary information

    Supplementary data are available at Bioinformatics online.

     
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  3. Abstract. The number and quality of ocean pH measurements have increasedsubstantially over the past few decades such that trends, variability, andspatial patterns of change are now being evaluated. However, comparing pHchanges across domains with different initial pH values can be misleadingbecause a pH change reflects a relative change in the hydrogen ionconcentration ([H+], expressed in mol kg−1) rather than anabsolute change in [H+]. We recommend that [H+] be used inaddition to pH when describing such changes and provide three examplesillustrating why. 
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  4. Abstract

    Buffers of known quality for the calibration of seawater pHTmeasurements are not widely or commercially available. Although there exist published compositions for the 0.04 mol kg‐H2O−1equimolar buffer 2‐amino‐2‐hydroxymethyl‐1,3‐propanediol (TRIS)‐TRIS · H+in synthetic seawater, there are no explicit procedures that describe preparing this buffer to achieve a particular pHTwith a known uncertainty. Such a procedure is described here which makes use of easily acquired laboratory equipment and techniques to produce a buffer with a pHTwithin 0.006 of the published pHTvalue originally assigned by DelValls and Dickson (1998), 8.094 at 25°C. Such a buffer will be suitable for the calibration of pH measurements expected to fulfil the “weather” uncertainty goal of the Global Ocean Acidification Observation Network of 0.02 in pHT, an uncertainty goal appropriate to “identify relative spatial patterns and short‐term variation.”

     
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  5. Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above. 
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