{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001629811,0.0009577555,0.0004334926,0.002889872,0.001239201,0.001312183,0.000805421,0.0014101,0.006062387],"category_scores_gemma":[0.002702679,0.0004907079,0.0005865166,0.0008113907,0.001791403,0.001063715,0.001368945,0.002021866,0.003519794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005489207,"about_ca_system_score_gemma":0.001195286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00134412,"about_ca_topic_score_gemma":0.002062591,"domain_scores_codex":[0.9992504,0.000197794,0.0000685515,0.0001624099,0.0002591643,0.00006174441],"domain_scores_gemma":[0.9976611,0.0006864262,0.0001082491,0.0006392319,0.0007188675,0.0001861783],"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":[0.0002422458,0.0001031071,0.009380341,0.0004338921,0.00003281515,0.0008698796,0.0004713192,0.0002549978,0.9432123,0.005926989,0.001193248,0.03787883],"study_design_scores_gemma":[0.00003827346,0.0002481004,0.0138292,0.0002043781,0.0001013785,0.004737774,0.0006672351,0.002690756,0.9111373,0.009389295,0.05692025,0.00003611949],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1717018,0.01929689,0.7507926,0.002937268,0.001531122,0.001375536,0.002168703,0.003179095,0.04701696],"genre_scores_gemma":[0.5219097,0.01470135,0.435635,0.00345707,0.0006207261,0.001108428,0.00325523,0.000829595,0.01848288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006062387,"threshold_uncertainty_score":0.02028072,"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."}}