{"id":"W2524140413","doi":"","title":"ANALYSIS OF REPETITIVE DNA BY FLOW CYTOMETRY USING CHROMOSOME FLOW FISH","year":2011,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Terry Fox Research Institute","funders":"","keywords":"Fish <Actinopterygii>; Flow cytometry; Flow (mathematics); Chromosome; Biology; Genetics; Fishery; Mechanics; Physics; Gene","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":[0.0003616094,0.0001997549,0.0003315288,0.00008652383,0.0001379378,0.00002700033,0.000702018,0.0001131866,0.00002259013],"category_scores_gemma":[0.00001881151,0.0001628891,0.00009268158,0.0004281477,0.0001196572,0.00001382699,0.000965736,0.0001076905,6.632388e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005035703,"about_ca_system_score_gemma":0.00001354085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001878458,"about_ca_topic_score_gemma":0.0003197918,"domain_scores_codex":[0.9984977,0.0001417735,0.0002978369,0.0006375695,0.0001133478,0.000311764],"domain_scores_gemma":[0.9989219,0.00005150424,0.0001658202,0.0007196421,0.00003601049,0.0001051496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003538869,0.0002844649,0.2141774,0.0002282544,0.002690315,0.00002090344,0.001400488,0.002301967,0.7538577,0.000008658506,0.0004874933,0.02418841],"study_design_scores_gemma":[0.0004508166,0.0003619782,0.08962344,0.0001798673,0.001002149,0.00001687107,0.0004824434,0.8812284,0.02326654,0.00004101458,0.002723301,0.0006231384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884481,0.0003750735,0.009168548,0.000006831817,0.00006782272,0.00007288322,0.001114766,0.00001884811,0.0007271634],"genre_scores_gemma":[0.9876159,0.000233428,0.006078274,0.0002130721,0.0001653205,0.000001656488,0.005645654,0.00001443895,0.00003227954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8789265,"threshold_uncertainty_score":0.6642426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02726114713036774,"score_gpt":0.2519700490500067,"score_spread":0.224708901919639,"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."}}