{"id":"W4402320855","doi":"10.1177/00236772241247105","title":"Depicting variability and uncertainty using intervals and error bars","year":2024,"lang":"en","type":"article","venue":"Laboratory Animals","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Statistics; Notation; Range (aeronautics); Variation (astronomy); Interval (graph theory); Population; Population mean; Confidence interval; Sample (material); Mathematics; Econometrics; Demography; Arithmetic; Combinatorics","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":[0.000734229,0.0001553096,0.0001776856,0.0000414364,0.000097371,0.00008638451,0.0000695178,0.0001311745,0.0000228869],"category_scores_gemma":[0.0001189201,0.0001488917,0.00004947444,0.0002048892,0.0001115434,0.000007922994,0.0001377606,0.00008534332,0.000001806105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001943228,"about_ca_system_score_gemma":0.00008153242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009866955,"about_ca_topic_score_gemma":0.00001589722,"domain_scores_codex":[0.9988488,0.0001887347,0.000206713,0.0004831281,0.00007731409,0.0001953275],"domain_scores_gemma":[0.9995127,0.00003571531,0.00004228409,0.0002320158,0.00007749486,0.00009979822],"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":[0.00003353416,0.00001589045,0.02674148,0.0001511204,0.0002274955,0.00001384425,0.0001415099,0.0008231897,0.9694266,0.0004179503,0.0002311865,0.00177618],"study_design_scores_gemma":[0.001931196,0.001492793,0.09802472,0.000856117,0.002058598,0.0003024922,0.002777864,0.190341,0.4924995,0.003744643,0.20208,0.003891164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921203,0.006779341,0.0007303959,0.00005793857,0.00008894881,0.00008826166,0.00003144803,0.0000291427,0.00007425785],"genre_scores_gemma":[0.9981099,0.00009354568,0.00142894,0.00009920799,0.0002012732,0.000005461267,0.000008504967,0.00002262873,0.00003048071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4769271,"threshold_uncertainty_score":0.6071628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137327175505871,"score_gpt":0.275528335927043,"score_spread":0.2617956183764559,"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."}}