{"id":"W6931417871","doi":"10.5281/zenodo.5149630","title":"A Knowledge Mapping with Trends, Emerging Scenario & Future possibilities for creating a True Digital India","year":2021,"lang":"en","type":"dissertation","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Intraperitoneal and Appendiceal Malignancies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universität Bielefeld; Simon Fraser University","keywords":"Field (mathematics); Emerging technologies; Key (lock); Knowledge production; Knowledge base; Digital transformation; Knowledge-based systems","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002539074,0.0003504347,0.0004792138,0.0004671618,0.002068431,0.001108626,0.0003726188,0.000204863,0.003807869],"category_scores_gemma":[0.0003040655,0.0003156108,0.0001708216,0.000776551,0.0001011916,0.0002689481,0.0001931652,0.0005218003,0.000304824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000197588,"about_ca_system_score_gemma":0.00004549316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001679048,"about_ca_topic_score_gemma":0.000005029959,"domain_scores_codex":[0.9978932,0.00008373758,0.0004182073,0.0006617181,0.000400871,0.0005422828],"domain_scores_gemma":[0.9980658,0.00003626238,0.0002239884,0.0003692718,0.001092223,0.0002124629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002401233,0.0009217572,0.00004938267,0.007218755,0.0009473792,0.0003325493,0.09479095,0.000007067247,0.009051558,0.006571726,0.06532015,0.8123875],"study_design_scores_gemma":[0.001529477,0.0009111529,0.002225699,0.001811487,0.0001566249,0.0004653331,0.05255597,0.000105223,0.0009249678,0.00005375731,0.938751,0.000509296],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4434095,0.002101349,0.0002786377,0.0006817917,0.000561861,0.001585841,0.001188463,0.00118955,0.549003],"genre_scores_gemma":[0.7718151,0.0002098975,0.001121888,0.0001594606,0.002830834,0.000001566925,0.09794129,0.004482585,0.1214373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8734308,"threshold_uncertainty_score":0.9999296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02084471336903592,"score_gpt":0.262327679592242,"score_spread":0.241482966223206,"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."}}