{"id":"W2325353308","doi":"10.1097/01.pat.0000454054.85406.3a","title":"Application of cytological samples for molecular biology","year":2014,"lang":"en","type":"article","venue":"Pathology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cytology; Computational biology; Biology; Cancer; Pathology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001526734,0.00007450845,0.0001446306,0.00002320495,0.00002187605,0.000002023392,0.000122265,0.0001591072,0.000003222501],"category_scores_gemma":[0.0003447128,0.00007085189,0.00006623211,0.00002608965,0.0001102042,3.909818e-7,0.00006012335,0.00002628384,0.000002786634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000037065,"about_ca_system_score_gemma":0.00001796224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007542821,"about_ca_topic_score_gemma":0.000009882175,"domain_scores_codex":[0.9994041,0.00004131722,0.0001512311,0.0002401245,0.00001906631,0.0001441157],"domain_scores_gemma":[0.9995165,0.00006551514,0.00007710679,0.0002449028,0.00006611986,0.00002982133],"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":[0.00004269251,0.00003030461,0.004770369,0.000009644011,0.000008909929,2.740079e-7,0.000006110647,0.00006260663,0.9268232,0.05694398,0.0001424572,0.01115945],"study_design_scores_gemma":[0.001025276,0.001528588,0.005737158,0.000002272686,0.00003578798,0.00003180277,0.00001386299,0.000610619,0.7640799,0.0436185,0.1830792,0.0002370831],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4013876,0.0002433659,0.5976958,0.0001126608,0.0000657514,0.0001251929,0.00004764367,0.000004314285,0.0003176777],"genre_scores_gemma":[0.9840885,0.00005586358,0.01491855,0.0004488879,0.000122843,0.00009261115,0.0002534191,0.00001010826,0.000009234632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5827772,"threshold_uncertainty_score":0.2889256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097318276912076,"score_gpt":0.2807018377959712,"score_spread":0.2697286550268505,"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."}}