{"id":"W4416739914","doi":"10.3390/cancers17233797","title":"Tissue Microarray-Based Digital Spatial Profiling of Benign Breast Lobules and Breast Cancers: Feasibility, Biological Coherence, and Cross-Platform Benchmarks","year":2025,"lang":"en","type":"article","venue":"Cancers","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Cancer Institute","keywords":"Profiling (computer programming); Risk stratification; Breast tissue; Digital pathology; Sampling (signal processing); Breast imaging; Breast tumours; Breast cancer","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":[0.005589053,0.0004430411,0.0004398106,0.001313751,0.0004589392,0.001054444,0.0005551383,0.0005320553,0.001066521],"category_scores_gemma":[0.005599472,0.0003893601,0.000387053,0.001074192,0.0006495183,0.0004844897,0.0009141272,0.0004150639,0.0003964227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005629548,"about_ca_system_score_gemma":0.0003597949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001182377,"about_ca_topic_score_gemma":0.002440683,"domain_scores_codex":[0.995818,0.001326746,0.0002865157,0.001075959,0.001294586,0.0001982953],"domain_scores_gemma":[0.9962,0.001382545,0.0006560282,0.0007843921,0.0008667578,0.000110243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001019983,0.0001745182,0.1967973,0.0004313302,0.0003535526,0.0001344895,0.0004681536,0.004774531,0.7430502,0.0008376232,0.0007918957,0.05116648],"study_design_scores_gemma":[0.00005175007,0.0009255392,0.4830175,0.00006385559,0.0004650478,0.00145612,0.0005918007,0.04149376,0.4625657,0.001377112,0.007916704,0.00007507263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8632542,0.002419087,0.1283838,0.0002810135,0.0000738048,0.0002617508,0.001576005,0.0005459998,0.003204392],"genre_scores_gemma":[0.9023659,0.0005513319,0.09376679,0.0001890086,0.00005283146,0.0003961642,0.001568137,0.00008692627,0.001022995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005589053,"threshold_uncertainty_score":0.02955806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01856528490967006,"score_gpt":0.2816067340445425,"score_spread":0.2630414491348724,"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."}}