{"id":"W4233351450","doi":"10.4000/communication.10292","title":"Marcel DANESI (2016), Concise Dictionary of Popular Culture","year":2019,"lang":"en","type":"article","venue":"Communication","topic":"European Cultural and National Identity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Art; Artificial intelligence; Linguistics; Computer science; History; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003535453,0.00003877843,0.00006557192,0.00002268757,0.000219006,0.00001792293,0.0003672169,0.00004179996,0.0003433934],"category_scores_gemma":[0.00009526259,0.00003341135,0.00003952352,0.0001416539,0.0001083744,0.0002584501,0.00007793953,0.00007877086,0.0002715077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263889,"about_ca_system_score_gemma":0.00003691865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004414722,"about_ca_topic_score_gemma":0.0001623203,"domain_scores_codex":[0.9992908,0.0002336801,0.0001270271,0.00007175252,0.0002115136,0.00006522756],"domain_scores_gemma":[0.9993623,0.0000285115,0.00009827202,0.0002708951,0.0002100144,0.0000299714],"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":[0.00004321187,0.0002898915,0.1088542,0.00006241993,0.0000536316,9.966415e-7,0.0231807,0.00003662685,0.0152577,0.718277,0.1273485,0.006595211],"study_design_scores_gemma":[0.0002540818,0.00002155362,0.1107622,0.00005729844,0.00001428364,8.460913e-7,0.002782413,0.00004167941,0.0001558661,0.006993547,0.8787966,0.0001196003],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7433184,0.004928943,0.00001841877,0.003441364,0.000225891,0.0003594715,0.00001343838,0.00008273939,0.2476113],"genre_scores_gemma":[0.9642705,0.002245873,0.0003221037,0.00007605746,0.00003819203,0.000002898451,0.00007954551,0.000003402264,0.03296139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7514482,"threshold_uncertainty_score":0.3759917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02473691440981678,"score_gpt":0.2994183728281262,"score_spread":0.2746814584183094,"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."}}