{"id":"W4407868588","doi":"10.1101/2025.02.19.638201","title":"Multi-Modal Disentanglement of Spatial Transcriptomics and Histopathology Imaging","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Vector Institute; University of Toronto; University Health Network","funders":"","keywords":"Modal; Histopathology; Computer science; Materials science; Medicine; Pathology; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004411378,0.0009274817,0.0006832448,0.001411615,0.0005854032,0.001407367,0.001121991,0.0008596609,0.003022209],"category_scores_gemma":[0.007999584,0.0005958538,0.001790764,0.001205571,0.001128638,0.001489538,0.002629458,0.001739082,0.001065704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009154733,"about_ca_system_score_gemma":0.001896493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006648175,"about_ca_topic_score_gemma":0.01114718,"domain_scores_codex":[0.9984185,0.0005758814,0.00005913503,0.0004699044,0.0003612445,0.0001153996],"domain_scores_gemma":[0.9967864,0.001441753,0.0003641354,0.000779825,0.0004479029,0.0001801837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001506805,0.000350972,0.04694214,0.0008155325,0.0008725359,0.0004956881,0.0006187079,0.3363463,0.1854212,0.03784686,0.02305306,0.3657301],"study_design_scores_gemma":[0.00004059216,0.00010585,0.01522608,0.00004732426,0.0001065533,0.0004346686,0.0001296729,0.8805138,0.03256446,0.05739541,0.01335012,0.00008548445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04638147,0.0005475431,0.945915,0.000503846,0.0000728505,0.00007635104,0.002085433,0.003128687,0.001288781],"genre_scores_gemma":[0.5058641,0.0004904289,0.4793285,0.00054641,0.0001435869,0.0003221967,0.007968844,0.001351321,0.003984581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006648175,"threshold_uncertainty_score":0.02332991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007525874220976353,"score_gpt":0.2367267958237856,"score_spread":0.2292009216028092,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}