Background: Reference-based deconvolution estimates cell-type proportions from bulk profiles. Incomplete references are its dominant error source, yet every current remedy ends in a point estimate. We separate the operator provenance that reproduces an estimate from the information and precision that identify its target. Results: Crossing two operator histories at one reduced reference shows the estimator is not unique: 28.2% of 196,420 sample-deletion pairs differed by >0.1 total variation, and locking all learned components made paths identical. Across nine cohorts, operator history reversed 31 of 952 associations and changed significance for 126. Fixing the operator does not identify the target: observationally equivalent completions fill the open simplex and reverse retained-type rankings. Shared structure cannot tighten inherited bounds, and one to six uncalibrated views gave identical bounds. A profile library contracted estimator-output envelopes by 98.93% yet covered the full-reference effect for only 42.77% (19 wrong-sign certificates), while conditional sharp bounds stayed at [-1, 1]. Treating absolute RNA yields as exact collapsed intervals to points yet covered none of seven flow-measured targets. Contraction without coverage is false certainty. Calibrated cross-modal anchors contract width (0.51 at six types) but never validly certify a sign. Absolute quantification restores identification in principle, and a decisive sign in peripheral blood mononuclear cells requires {+/-}2.6% proxy accuracy with near-total contraction of donor-heterogeneity and dynamic-range envelopes. Conclusions: Incomplete-reference deconvolution is an identification problem, not only an estimation problem. Remedies must be judged by shrinkage, coverage, certification and false certification against held-out targets. fitdrop implements this scoring and a precision frontier for planning a decisive measurement.
Jiang, H., Gao, F., Liu, P., Wu, Y., Jie, Y., Li, Y., Jiang, Y.
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