{"id":"W2951879533","doi":"10.1186/s13104-018-3507-2","title":"GrapHi-C: graph-based visualization of Hi-C datasets","year":2018,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Graph; Computer science; Computational biology; Data mining; Biology; Theoretical computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00178798,0.00169031,0.001010835,0.005184755,0.0008137946,0.002712723,0.001826739,0.001071572,0.02593213],"category_scores_gemma":[0.00830218,0.0005367778,0.001128496,0.004532101,0.0004435088,0.001852595,0.001892837,0.002444235,0.00416026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009111054,"about_ca_system_score_gemma":0.001565324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00590197,"about_ca_topic_score_gemma":0.007128283,"domain_scores_codex":[0.9991474,0.0002497305,0.00008588571,0.0001814033,0.0002662378,0.00006940587],"domain_scores_gemma":[0.995627,0.002573409,0.0003786215,0.0005447264,0.0006888339,0.0001873564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002170529,0.0005499879,0.01112267,0.008716617,0.001063083,0.001049031,0.002859944,0.03486902,0.04662473,0.0407841,0.6633841,0.1868063],"study_design_scores_gemma":[0.0008144576,0.0003288399,0.02920781,0.001063369,0.0003970525,0.0009542424,0.001415709,0.2899379,0.05436791,0.09702757,0.5238608,0.0006243523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.03624785,0.001381438,0.3424347,0.002216543,0.0006867489,0.0009748195,0.411245,0.1926916,0.01212128],"genre_scores_gemma":[0.1220417,0.001812076,0.5166606,0.0006383871,0.0001898355,0.002658477,0.3323754,0.01959252,0.004031006],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02593213,"threshold_uncertainty_score":0.08675164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08039961376908901,"score_gpt":0.3956879777125182,"score_spread":0.3152883639434292,"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."}}