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Here, we address this challenge by analysing H\u202f\n                    <jats:sc>I<\/jats:sc>\n                    intensity maps of about 100 deg\n                    <jats:sup>2<\/jats:sup>\n                    at redshift\n                    <jats:italic>z<\/jats:italic>\n                    \u2004\u2248\u20040.4 collected by the MeerKAT radio telescope, an SKA Observatory (SKAO) precursor, with a combined 10.5-hour observation. Using unsupervised statistical methods, we removed the contaminating foreground emission and systematically tested, step-by-step, some common pre-processing choices to facilitate the cleaning process. We also introduced and tested a novel multiscale approach: the data were redundantly decomposed into subsets referring to different spatial scales (large and small), where the cleaning procedure was performed independently. We confirm the detection of the H\u202f\n                    <jats:sc>I<\/jats:sc>\n                    cosmological signal in cross-correlation with an ancillary galactic data set, without the need to correct for signal loss. In the best set-up we achieved, we were able to constrain the H\u202f\n                    <jats:sc>I<\/jats:sc>\n                    distribution through the combination of its cosmic abundance (\u03a9\n                    <jats:sub>\n                      H\u202f\n                      <jats:sc>I<\/jats:sc>\n                    <\/jats:sub>\n                    ) and linear clustering bias (\n                    <jats:italic>b<\/jats:italic>\n                    <jats:sub>\n                      H\u202f\n                      <jats:sc>I<\/jats:sc>\n                    <\/jats:sub>\n                    ) up to a cross-correlation coefficient (\n                    <jats:italic>r<\/jats:italic>\n                    ). We measured \u03a9\n                    <jats:sub>\n                      H\u202f\n                      <jats:sc>I<\/jats:sc>\n                    <\/jats:sub>\n                    <jats:italic>b<\/jats:italic>\n                    <jats:sub>\n                      H\u202f\n                      <jats:sc>I<\/jats:sc>\n                    <\/jats:sub>\n                    <jats:italic>r<\/jats:italic>\n                    = [0.93 \u00b1 0.17] \u00d7 10\n                    <jats:sup>\u22123<\/jats:sup>\n                    with a \u22486\n                    <jats:italic>\u03c3<\/jats:italic>\n                    confidence, which is independent of scale cuts at both edges of the probed scale range (0.04\u2004\u2272\u2004\n                    <jats:italic>k<\/jats:italic>\n                    \u2004\u2272\u20040.3\u2006\n                    <jats:italic>h<\/jats:italic>\n                    Mpc\n                    <jats:sup>\u22121<\/jats:sup>\n                    ), corroborating its robustness. Our new pipeline has successfully found an optimal compromise in separating contaminants without incurring a catastrophic signal loss. This development instills an added degree of confidence in the outstanding science we can deliver with MeerKAT on the path towards H\u202f\n                    <jats:sc>I<\/jats:sc>\n                    intensity mapping surveys with the full SKAO.\n                  <\/jats:p>","DOI":"10.1051\/0004-6361\/202453461","type":"journal-article","created":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T18:43:46Z","timestamp":1760381026000},"page":"A222","source":"Crossref","is-referenced-by-count":7,"title":["Hydrogen intensity mapping with MeerKAT: Preserving cosmological signal by optimising contaminant separation"],"prefix":"10.1051","volume":"703","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5287-0065","authenticated-orcid":false,"given":"I. 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