{"id":"W4225764001","doi":"10.1371/journal.pone.0262717","title":"Evaluation of deep convolutional neural networks for in situ hybridization gene expression image representation","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Centre for Addiction and Mental Health Foundation; Nvidia","keywords":"Discriminative model; Artificial intelligence; Convolutional neural network; Gene expression; Pattern recognition (psychology); Computer science; Computational biology; In situ hybridization; Biology; Gene; Machine learning; Genetics","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":[0.0004317815,0.00005957493,0.00009024877,0.0000381535,0.00006883208,0.000005789859,0.00006985814,0.00003787122,0.00003022193],"category_scores_gemma":[0.0001132019,0.00007023584,0.00003884988,0.00007768648,0.00002058416,0.000006211173,0.00003664273,0.00005063625,1.521335e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003793306,"about_ca_system_score_gemma":0.00003540393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001030531,"about_ca_topic_score_gemma":0.00002275669,"domain_scores_codex":[0.9990364,0.0001570646,0.0001880929,0.0001909708,0.0003298916,0.00009753635],"domain_scores_gemma":[0.9995149,0.00001546054,0.00008781299,0.0001229193,0.0002405548,0.00001839461],"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":[0.0001874395,0.0004498428,0.004240787,0.00001264792,0.00002532976,1.671228e-7,0.00003992922,0.04069734,0.9536195,0.000005868962,0.00003471706,0.0006864725],"study_design_scores_gemma":[0.0009671659,0.0001278644,0.002582908,0.000005123682,0.00005689911,6.150148e-7,0.00002898906,0.3006271,0.6954622,0.00007606333,0.00000508734,0.00005995476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96323,0.0003739848,0.03575135,0.00003950834,0.00006804631,0.0004366002,0.00002237476,0.000004945777,0.00007316766],"genre_scores_gemma":[0.9951488,0.0000223004,0.003127805,0.00003876194,0.0001144992,0.0001738019,0.001344236,0.00001186833,0.00001794993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2599298,"threshold_uncertainty_score":0.2864135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05276219637594313,"score_gpt":0.2683558563759552,"score_spread":0.2155936600000121,"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."}}