{"id":"W2557953210","doi":"10.1002/path.4847","title":"The molecular basis of breast cancer pathological phenotypes","year":2016,"lang":"en","type":"article","venue":"The Journal of Pathology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"U.S. National Library of Medicine; National Institute of Environmental Health Sciences; National Cancer Institute; National Institutes of Health; Klarman Family Foundation","keywords":"Breast cancer; Transcriptome; Biology; Phenotype; Cancer; Pathology; Gene expression profiling; Oncology; Medicine; Computational biology; Bioinformatics; Internal medicine; Gene; Gene expression; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005899862,0.00008459695,0.0001468542,0.00001836036,0.00006125009,0.000004950742,0.0003501962,0.0000830028,0.00002599771],"category_scores_gemma":[0.0002023135,0.00003436275,0.0001070873,0.0000404102,0.0003087899,0.000001834701,0.0001078077,0.00007704278,0.00000226546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000128336,"about_ca_system_score_gemma":0.00009622694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000655008,"about_ca_topic_score_gemma":0.00002185658,"domain_scores_codex":[0.9992144,0.0001683881,0.0002785049,0.00008074084,0.00009677779,0.0001611715],"domain_scores_gemma":[0.9990515,0.0001497946,0.0002984953,0.0002532132,0.0002059931,0.00004103372],"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":[0.0003294249,0.00002972858,0.0021793,0.000002351788,0.00004789791,0.00003581031,0.00003826331,0.00004717509,0.9746085,0.0008299773,0.00118826,0.0206633],"study_design_scores_gemma":[0.002370002,0.001860129,0.1025025,0.00007541289,0.0003204639,0.00492067,0.0002758768,0.000007264106,0.8435057,0.007025069,0.03680348,0.0003333997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859794,0.005884509,0.002883608,0.004691051,0.0003053623,0.00005046372,0.0000557799,0.000001152834,0.0001487046],"genre_scores_gemma":[0.9906139,0.008526656,0.0001377039,0.0003849044,0.0002590392,0.000002559783,5.193535e-7,0.000009711062,0.00006501411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1311028,"threshold_uncertainty_score":0.1401272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007079787646189972,"score_gpt":0.2441299204643393,"score_spread":0.2370501328181493,"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."}}