{"id":"W2141817946","doi":"10.1155/2003/262918","title":"Risk Biomarker Assessment for Breast Cancer Progression: Replication Precision of Nuclear Morphometry","year":2003,"lang":"en","type":"article","venue":"Analytical Cellular Pathology","topic":"AI in cancer detection","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"National Cancer Institute; National Institutes of Health","keywords":"Feulgen stain; Pathology; Breast cancer; Histopathology; Stain; Nuclear DNA; Biology; Medicine; Cancer; Staining; Internal medicine","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":[0.06130657,0.0008605131,0.001434127,0.002582169,0.0008373947,0.002178191,0.001076906,0.001215172,0.0004961338],"category_scores_gemma":[0.1649377,0.0005462138,0.000844817,0.001991096,0.002127751,0.001840688,0.001887517,0.001063491,0.0003668465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005852149,"about_ca_system_score_gemma":0.0006875618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229234,"about_ca_topic_score_gemma":0.001347475,"domain_scores_codex":[0.9551843,0.02568569,0.003173696,0.006910007,0.008413255,0.0006329895],"domain_scores_gemma":[0.8437805,0.08274769,0.0174843,0.04159515,0.01387822,0.0005141515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001638286,0.0001855061,0.7337537,0.0006627331,0.001936986,0.0003636487,0.00263617,0.01026447,0.07603271,0.005319297,0.0008569034,0.1663495],"study_design_scores_gemma":[0.0001130693,0.002401888,0.8102409,0.0002458483,0.002627165,0.002921757,0.0007102704,0.03708394,0.1105175,0.0218113,0.01105756,0.0002688275],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6143836,0.01308083,0.3638325,0.0009933213,0.0003095925,0.0004504299,0.0006110694,0.0007468498,0.005591817],"genre_scores_gemma":[0.9598719,0.0004654441,0.03846231,0.0001131971,0.0001210091,0.0001439263,0.0002574337,0.00007543221,0.0004892284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06130657,"threshold_uncertainty_score":0.324224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218421462256762,"score_gpt":0.3289193682651577,"score_spread":0.3070772220394815,"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."}}