{"id":"W4407624627","doi":"10.2196/65371","title":"Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Component (thermodynamics); Computer science; Selection (genetic algorithm); Data mining; Artificial intelligence; Natural language processing; Data science; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05446733,0.002319892,0.003135018,0.007593459,0.001355877,0.003246451,0.002894195,0.001789485,0.003670351],"category_scores_gemma":[0.1828587,0.001379426,0.003756093,0.005456321,0.0008708544,0.003526847,0.002246821,0.002479051,0.00132323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003936103,"about_ca_system_score_gemma":0.01532931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01041232,"about_ca_topic_score_gemma":0.02207456,"domain_scores_codex":[0.9793327,0.0119239,0.003846401,0.00246046,0.002184893,0.0002515831],"domain_scores_gemma":[0.8214895,0.1476272,0.00782811,0.0093836,0.01288379,0.0007878341],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002083541,0.0004921494,0.01773002,0.009663749,0.002216188,0.0002449514,0.0007154698,0.06855973,0.005005217,0.003165142,0.02166597,0.8684579],"study_design_scores_gemma":[0.00114873,0.0003638295,0.00438572,0.001102628,0.001872452,0.0002576478,0.000207829,0.9581853,0.008964906,0.01255144,0.01084356,0.0001159832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04864287,0.005457538,0.9000072,0.002660532,0.0004043372,0.01190736,0.006083434,0.02351958,0.001317155],"genre_scores_gemma":[0.09116265,0.0006760953,0.8969452,0.0005405171,0.0000793253,0.006148552,0.003777809,0.0002776361,0.0003921167],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9455327,"threshold_uncertainty_score":0.2880542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2033671673957739,"score_gpt":0.4528848757690538,"score_spread":0.2495177083732799,"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."}}