{"id":"W4380371034","doi":"10.2196/48631","title":"Introducing JMIR Bioinformatics and Biotechnology: A Platform for Interdisciplinary Collaboration and Cutting-Edge Research","year":2023,"lang":"en","type":"editorial","venue":"JMIR Bioinformatics and Biotechnology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Informatics; Genomics; Data science; Health informatics; Bioinformatics; Engineering; Biology; Computer science; Health care; Political science; Genome; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00181077,0.0007982829,0.0009353361,0.00117196,0.0009009254,0.0004660976,0.0006879895,0.006005402,0.00000219922],"category_scores_gemma":[0.0008533226,0.0007250601,0.0001264826,0.0007660691,0.001485413,0.0000724768,0.003726611,0.001788929,0.00001823012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001013492,"about_ca_system_score_gemma":0.0003638812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001038133,"about_ca_topic_score_gemma":0.0001111461,"domain_scores_codex":[0.995995,0.00003961079,0.001479922,0.0008151851,0.0004476913,0.001222591],"domain_scores_gemma":[0.9970087,0.0004132171,0.0007810835,0.00106206,0.0004980959,0.00023684],"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":[0.0002823623,0.00005701282,0.000007958869,0.002527313,0.0002665195,0.000003857857,0.00142865,0.000006523954,0.002108218,0.001725243,0.8779348,0.1136516],"study_design_scores_gemma":[0.002146848,0.002930461,0.000009718578,0.000508022,0.00009456596,0.00007638054,0.007713873,0.03475134,0.002887686,0.002692776,0.9449965,0.001191787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.1534615,0.01653325,0.05021427,0.03850292,0.6896971,0.03355017,0.01252375,0.002929501,0.002587488],"genre_scores_gemma":[0.04467552,0.1316084,0.2678263,0.00129661,0.5025687,0.008269002,0.03630264,0.001782089,0.005670801],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.217612,"threshold_uncertainty_score":0.9995201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491582163907395,"score_gpt":0.323829898327464,"score_spread":0.30891407668839,"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."}}