{"id":"W2019498472","doi":"10.1038/modpathol.3880120","title":"Laser Capture Microdissection–Guided Fluorescence In Situ Hybridization and Flow Cytometric Cell Cycle Analysis of Purified Nuclei from Paraffin Sections","year":2000,"lang":"en","type":"article","venue":"Modern Pathology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Calgary Laboratory Services; University of Calgary","funders":"Medical Research Council; Medical Research Council Canada; Terry Fox Foundation; Calgary Laboratory Services","keywords":"Fluorescence in situ hybridization; Laser capture microdissection; Biology; Microdissection; Flow cytometry; Population; In situ; Molecular biology; Pathology; Gene; Chromosome; Genetics; Gene expression; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009896942,0.0001340951,0.0002278838,0.0002677453,0.00006064872,0.000008907648,0.0001236008,0.0002659755,0.00005433735],"category_scores_gemma":[0.00001790393,0.0001406584,0.00008599543,0.0006451983,0.00009280488,0.000004069505,0.00004451616,0.0001047617,0.00000349416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001202537,"about_ca_system_score_gemma":0.00001983438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001690025,"about_ca_topic_score_gemma":0.0004401814,"domain_scores_codex":[0.9989384,0.0001014912,0.0002608033,0.0004780153,0.00005193926,0.0001693982],"domain_scores_gemma":[0.9994447,0.00001296213,0.00007951017,0.0003671296,0.00005137008,0.00004427719],"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":[0.00002521947,0.0001246582,0.005030546,0.000003359837,0.00005579948,0.000007230064,0.00010146,0.005359045,0.9848232,0.000006962065,0.0001382699,0.004324306],"study_design_scores_gemma":[0.0005835176,0.0001090904,0.06696725,0.00000492186,0.0002504463,0.00002886596,0.00003073414,0.02056181,0.9102137,0.0003021327,0.00066662,0.0002808774],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648252,0.0003960283,0.03384241,0.00005842792,0.0000175465,0.0001703531,0.0001222224,0.0000206009,0.000547277],"genre_scores_gemma":[0.9927456,0.0004092641,0.005633927,0.000129644,0.00002312671,0.00005097597,0.0008120691,0.00001440082,0.0001810153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07460941,"threshold_uncertainty_score":0.5735883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005700663047259416,"score_gpt":0.2309258123421108,"score_spread":0.2252251492948514,"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."}}