{"id":"W4417183891","doi":"10.1093/bib/bbaf657","title":"SpaTM: topic models for inferring spatially informed transcriptional programs","year":2025,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Interpretability; Benchmarking; Spatial analysis; Cluster analysis; Crime analysis; Topic model","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002235227,0.001307763,0.001144135,0.001392685,0.0005995138,0.001449556,0.001975345,0.001897822,0.00230062],"category_scores_gemma":[0.00615653,0.0007511753,0.002923494,0.001860757,0.000832785,0.001925145,0.00139124,0.002687699,0.001330981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213859,"about_ca_system_score_gemma":0.001172427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008191884,"about_ca_topic_score_gemma":0.01238877,"domain_scores_codex":[0.9989964,0.0004166257,0.0000584864,0.0003179621,0.0001304063,0.00008010535],"domain_scores_gemma":[0.9965433,0.002778367,0.000167766,0.0001999198,0.0002286908,0.00008187667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000560189,0.0001180889,0.004869984,0.0005161995,0.000470026,0.0002974484,0.000614047,0.6737094,0.01701101,0.03513201,0.01617614,0.2505255],"study_design_scores_gemma":[0.00001244181,0.00001790186,0.0002996913,0.00001477569,0.00002704413,0.00003862394,0.00002401774,0.9757169,0.001198887,0.02073213,0.001904183,0.00001337418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008038711,0.0006722272,0.987599,0.0004410436,0.00006129942,0.00003463883,0.0009410075,0.001788461,0.0004236487],"genre_scores_gemma":[0.405144,0.002212895,0.5739496,0.0009525911,0.0007907269,0.001002726,0.008970729,0.001330341,0.005646333],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008191884,"threshold_uncertainty_score":0.0162884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02433102918432666,"score_gpt":0.2603119121612157,"score_spread":0.2359808829768891,"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."}}