{"id":"W4388525344","doi":"10.1108/978-1-80382-701-820231085","title":"Glossary","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"International Science and Diplomacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agència de Gestió d'Ajuts Universitaris i de Recerca; Canadian Institutes of Health Research; Università di Bologna; Alliance for Accelerating Excellence in Science in Africa; Canada Excellence Research Chairs, Government of Canada; Canada First Research Excellence Fund; Canada Research Chairs; Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; CHIST-ERA; European Commission","keywords":"Library science; Agency (philosophy); Political science; Management; Humanities; Sociology; Art; Social science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002822164,0.000075196,0.00008019777,0.00007417781,0.0002420335,0.0000642353,0.0003060504,0.000143784,0.009039057],"category_scores_gemma":[0.00005451301,0.00006706635,0.00008429724,0.00003020236,0.000204046,0.00009874794,0.00005152961,0.00009443571,0.01458011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007186714,"about_ca_system_score_gemma":0.0002095681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001069603,"about_ca_topic_score_gemma":0.002692555,"domain_scores_codex":[0.998965,0.000005819653,0.00009883074,0.0001664525,0.0006049115,0.0001589436],"domain_scores_gemma":[0.9996384,0.00007523213,0.00004283969,0.00008583548,0.00008096685,0.00007667435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[5.474736e-7,0.000001100902,0.000005910248,6.848343e-7,0.000005160698,0.0000112712,0.0002355673,1.310339e-7,4.663836e-7,0.9383099,0.05909884,0.002330441],"study_design_scores_gemma":[0.0000117779,0.000003344353,0.00001469038,0.00001068401,0.000002365327,1.234879e-7,0.00005222025,8.454281e-7,6.871737e-7,0.3675162,0.6323213,0.00006573897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000004030505,0.00001784275,0.000009028733,0.002146393,0.0006695972,0.0000754432,0.000006825257,0.0001960089,0.9968748],"genre_scores_gemma":[0.00064356,0.0001850334,0.00004249924,0.0006085609,0.0007439405,0.000001927368,0.00000819649,0.00001216332,0.9977541],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5732225,"threshold_uncertainty_score":0.9918668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07179607380287079,"score_gpt":0.3683334484330711,"score_spread":0.2965373746302003,"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."}}