{"id":"W4394527370","doi":"10.6084/m9.figshare.7518863","title":"Visibility of studies in social network analysis in South America: Its evolution and metrics from 1990 to 2013","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Education and Digital Technologies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visibility; Social network analysis; Geography; Computer science; Economic geography; Cartography; Genealogy; History; World Wide Web; Social media; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00289774,0.0002447935,0.0003091525,0.01327942,0.0006830127,0.002308828,0.000448907,0.0003704217,0.001568768],"category_scores_gemma":[0.01917686,0.0001783941,0.0004100603,0.02083175,0.000676106,0.002367855,0.002271742,0.0005983898,0.000193148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002202259,"about_ca_system_score_gemma":0.002695321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02586886,"about_ca_topic_score_gemma":0.02611342,"domain_scores_codex":[0.9983882,0.0003315747,0.0002657991,0.0003373974,0.0004831226,0.000194019],"domain_scores_gemma":[0.9759321,0.005233057,0.01144138,0.0007944935,0.004888078,0.001710968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006844054,0.0000314972,0.9384318,0.000583492,0.0001621845,0.0002255252,0.009150871,0.0002309476,0.0007264765,0.001312862,0.002953481,0.04612254],"study_design_scores_gemma":[0.000001920752,0.00001483708,0.9828495,0.0002579451,0.00004020479,0.0002298679,0.004947684,0.000216108,0.0001878723,0.0001985952,0.01104573,0.000009820374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9650475,0.01132635,0.0007928866,0.003142051,0.00008056216,0.00007435783,0.005681646,0.00004391956,0.01381076],"genre_scores_gemma":[0.9906951,0.004937152,0.0006694679,0.0001146131,0.000104821,0.00008835135,0.002517605,0.00001627537,0.000856541],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9867206,"threshold_uncertainty_score":0.0514366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1530181902349003,"score_gpt":0.4096951387292924,"score_spread":0.256676948494392,"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."}}