{"id":"W3137172717","doi":"10.1504/ijdmb.2020.10036329","title":"A network enhancement-based method for clustering of single cell RNA-seq data","year":2020,"lang":"en","type":"article","venue":"International Journal of Data Mining and Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Cluster analysis; Computer science; Similarity (geometry); Data mining; Node (physics); Noise (video); Artificial intelligence; Pattern recognition (psychology); Physics","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":[0.0004484213,0.00009128354,0.0001595944,0.00003168837,0.00002774788,0.00005060249,0.0009108718,0.00005473853,0.000004296882],"category_scores_gemma":[0.0001619381,0.00007975949,0.00003853092,0.00003618876,0.0000299737,0.00004734597,0.0003347502,0.00005263113,2.050836e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005453826,"about_ca_system_score_gemma":0.00008790326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003806792,"about_ca_topic_score_gemma":0.000006353621,"domain_scores_codex":[0.9990453,0.00001803805,0.0005295588,0.0001172584,0.0001842476,0.0001056497],"domain_scores_gemma":[0.9989876,0.00006413407,0.000450041,0.0002456931,0.0001869058,0.00006559311],"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":[0.001744085,0.0002650174,0.0009202693,0.0004821302,0.0005296996,0.000006846115,0.0008047593,0.002001959,0.6058518,0.000006128034,0.02838049,0.3590069],"study_design_scores_gemma":[0.002660903,0.001249959,0.00001511373,0.0002033166,0.0001229895,0.00003193244,0.000476423,0.8538492,0.1048926,0.000008227862,0.03627821,0.0002110775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02077669,0.0003199745,0.9772298,0.000535988,0.0003316815,0.00006548462,0.0005958356,0.000002344051,0.0001421474],"genre_scores_gemma":[0.1435731,0.000110783,0.8536635,0.0009236261,0.0005240917,4.75917e-7,0.0011829,0.00000951936,0.00001203467],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8518472,"threshold_uncertainty_score":0.3252498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09629500041666537,"score_gpt":0.3209526518611276,"score_spread":0.2246576514444623,"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."}}