{"id":"W4323314130","doi":"10.3390/su15054604","title":"Analysis of Countries in Terms of Artificial Intelligence Technologies: PROMETHEE and GAIA Method Approach","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); China; Competitive intelligence; Private sector; Investment (military); Index (typography); Economic growth; Business; Artificial intelligence; Engineering; Political science; Marketing; Economics; Computer science; Politics","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":[],"consensus_categories":[],"category_scores_codex":[0.002405992,0.0001229695,0.0004696333,0.0007559025,0.00004970638,0.00003635659,0.0007131314,0.0001116307,0.000009344967],"category_scores_gemma":[0.002632988,0.00009193722,0.00009657076,0.004561572,0.0007347319,0.0002347142,0.0005307051,0.0001368639,0.000001051067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000132343,"about_ca_system_score_gemma":0.0001468933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002070269,"about_ca_topic_score_gemma":0.00003431481,"domain_scores_codex":[0.9982381,0.0002109931,0.0005196711,0.0004939623,0.0002482281,0.0002890644],"domain_scores_gemma":[0.9982747,0.0004760974,0.0001247231,0.0007377217,0.0003592501,0.00002753206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001382,0.0005778619,0.07596238,0.001572381,0.0003561715,0.00001068669,0.02741307,0.004022699,0.0006560808,0.3495238,0.00006824905,0.5396984],"study_design_scores_gemma":[0.00004554493,0.0002007249,0.01016528,0.000009199075,0.0000555524,9.197062e-7,0.005354598,0.5920344,0.0163057,0.3755324,0.0001190377,0.00017662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1902238,0.00006904313,0.8077515,0.0007051202,0.00003454025,0.0005175051,0.000007059683,0.0002006523,0.0004907329],"genre_scores_gemma":[0.9849878,0.00003554974,0.01487673,0.000009482096,0.000003025589,0.00003355859,0.000001843983,0.000003957359,0.00004805474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7947639,"threshold_uncertainty_score":0.3749091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03050434567943078,"score_gpt":0.3144500929720109,"score_spread":0.2839457472925802,"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."}}