{"id":"W1938979978","doi":"10.2196/medinform.3982","title":"Using MEDLINE Elemental Similarity to Assist in the Article Screening Process for Systematic Reviews","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"MEDLINE; Systematic review; Computer science; Process (computing); Information retrieval; Medicine; Data science; Medical physics; Chemistry","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2212893,0.0002781968,0.003039189,0.0002642687,0.0001378197,0.0006741846,0.002408785,0.0001218184,0.0005110498],"category_scores_gemma":[0.1203816,0.0001082605,0.0006878045,0.001859368,0.00006168054,0.0005166149,0.0001643459,0.0002680699,0.0005603118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000700392,"about_ca_system_score_gemma":0.0001683523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004963757,"about_ca_topic_score_gemma":0.0000548012,"domain_scores_codex":[0.969923,0.004627189,0.01507558,0.0003120567,0.009610092,0.0004521143],"domain_scores_gemma":[0.9889767,0.003981359,0.00370334,0.001926051,0.0008515902,0.0005609485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001601796,0.001677861,0.0491018,0.09227268,0.0006970236,0.00004624683,0.238989,0.00383471,0.00002054222,0.009782743,0.5482905,0.05512673],"study_design_scores_gemma":[0.0008627646,0.0001087288,0.0002963801,0.003883388,0.0001922649,0.00005896801,0.05089164,0.9099876,0.00001541891,0.001946035,0.03145197,0.0003048563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.280889,0.0005798549,0.693397,0.004079031,0.0002978263,0.01765307,0.00002682385,0.00001797579,0.003059438],"genre_scores_gemma":[0.9100742,0.000005660158,0.07437694,0.01279119,0.0002925884,0.002088826,0.00002338494,0.00002098128,0.0003261766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9061529,"threshold_uncertainty_score":0.8870278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8496713948631475,"score_gpt":0.6142034858786365,"score_spread":0.235467908984511,"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."}}