{"id":"W806991377","doi":"10.4018/ijcini.2014070103","title":"Big Data Analytics on the Characteristic Equilibrium of Collective Opinions in Social Networks","year":2014,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Big data; Computer science; Data science; Computational intelligence; Collective intelligence; Analytics; Benchmarking; Cloud computing; Sentiment analysis; Fuzzy logic; Set (abstract data type); Data mining; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009200145,0.0001260337,0.0002277148,0.0002706363,0.00007171771,0.0001492857,0.001330319,0.00005163553,0.000003071603],"category_scores_gemma":[0.001215566,0.00008725967,0.00006483857,0.0003781544,0.0001536079,0.0003835052,0.0005574942,0.0005091919,0.000001817621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003863284,"about_ca_system_score_gemma":0.00009923056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003264241,"about_ca_topic_score_gemma":0.000003751013,"domain_scores_codex":[0.9984632,0.0001108951,0.0007370514,0.0001046704,0.0004275415,0.0001566478],"domain_scores_gemma":[0.995173,0.002755983,0.00071851,0.000134308,0.001174398,0.00004377176],"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":[0.0003323958,0.0001859146,0.001212002,0.00001807339,0.0003392933,0.00001670998,0.00415533,0.001912064,0.00001714599,0.03043519,0.0006993301,0.9606766],"study_design_scores_gemma":[0.0002794813,0.0002201064,0.00940283,0.0005756237,0.00001695649,0.00005957981,0.0003828002,0.9834269,0.0003137059,0.004966041,0.0002257556,0.0001302081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07891227,0.0001252335,0.9170053,0.000890832,0.001757046,0.0001151343,0.00003045632,0.00000734841,0.001156361],"genre_scores_gemma":[0.998139,0.0001193015,0.0006115655,0.0006185644,0.000475216,9.080233e-7,0.00001593867,0.00000384455,0.00001570603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9815149,"threshold_uncertainty_score":0.3558346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07114705649550866,"score_gpt":0.3194985598557693,"score_spread":0.2483515033602606,"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."}}