{"id":"W2117442262","doi":"10.1093/carcin/bgm129","title":"A bibliometric analysis of scientific production in cancer molecular epidemiology","year":2007,"lang":"en","type":"article","venue":"Carcinogenesis","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Epidemiology; Population; Ranking (information retrieval); European union; Medicine; Geography; Demography; Environmental health; Pathology; Business; Computer science; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":["metaresearch","bibliometrics"],"category_scores_codex":[0.08729813,0.0001536305,0.0008052398,0.9191524,0.0001306576,0.0002391547,0.001629048,0.0001570264,0.0003826848],"category_scores_gemma":[0.08917611,0.0001172376,0.0004128771,0.9814319,0.0004086453,0.0002878112,0.0003627621,0.0001531155,0.00003386501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002358075,"about_ca_system_score_gemma":0.0002349299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001059918,"about_ca_topic_score_gemma":0.0006695157,"domain_scores_codex":[0.9905377,0.0005082641,0.001576907,0.001270382,0.005205526,0.0009012139],"domain_scores_gemma":[0.9880067,0.005554834,0.0005256768,0.0012297,0.004328119,0.000355005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001714533,0.00009238585,0.7882769,0.000004679397,0.00007490427,0.000009519441,0.00004583182,0.00162758,0.02010322,0.0001365729,0.0003357781,0.1892755],"study_design_scores_gemma":[0.0001226109,0.00003567449,0.9577388,0.000003522395,0.00008905792,0.000001132291,0.0001008532,0.002179277,0.03809518,0.0008032834,0.0007107744,0.0001198895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844127,0.009220012,0.004465389,0.0003271836,0.0008351736,0.0002177976,0.00002961456,0.00001149069,0.0004806122],"genre_scores_gemma":[0.998517,0.0002622297,0.0006465571,0.00005514059,0.0000369442,0.00001506689,0.000007044545,0.000009076118,0.0004508846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1891556,"threshold_uncertainty_score":0.9398186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5861870334913493,"score_gpt":0.582801078536854,"score_spread":0.003385954954495229,"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."}}