Retention prediction is increasingly used as an orthogonal decision layer in LC–MS, GC–MS, metabolomics, environmental screening, pharmaceutical analysis, and forensic toxicology, yet retention values remain conditional on chromatographic mode, stationary phase, mobile phase, ionization state, derivatization status, and chemical-class coverage. This paper asks whether heterogeneous retention repositories can be organized into transferable quantitative structure–retention relationship (QSRR) evidence without permitting unsupported predictions to influence compound identification. Reliability-gated similarity cartography (RG-SC) answers this question by arranging RPLC, HILIC, GC, mixed-transfer, chiral, condition-diverse RPLC, drug-discovery screening, and forensic HRMS retention records as mode-resolved analytical evidence. Local neighbourhoods are accepted only when fingerprint similarity, distribution-coefficient proximity, retention-factor proximity, chemical-nature agreement, dual structural/retention screening, and second-dominant-interaction compatibility point to the same chromatographic environment. Retention estimates pass forward only when the local chemical map, chromatographic-system context, validation behaviour, and neighbourhood density are mutually consistent. RG-SC changes QSRR from unrestricted global prediction into a defensible analytical decision process: it separates incompatible systems, identifies sparse or stereochemically sensitive domains, supports retention-assisted candidate filtration, and withholds predictions when evidence is insufficient. Transferable retention modelling is therefore most reliable when handled as evidence-gated local cartography rather than extrapolation from pooled retention values.